NE Handbook Sensor Networks

NE Handbook Series

Sensor Networks

ROHM's vision of a connected society that uses sensor networks for processing and

transmitting information instantaneously over large distances is becoming a reality.

By combining a wide range of compact, high-performance sensors with industry-leading

microcontrollers and the latest wireless technologies, the ROHM Group is

able to provide complete sensing solutions optimized to application requirements.

Transforming society throughsensor network technologies

ROHMSensing

Solutions

Brigh

tness

UV H

all Temperature Geomagnetism Pressure Acceleration Gyro Touch Image Infrared

Lo

w Power M

CUs Wireless Communication MCUs Sensor Controllers

WiFi Bluetooth EnOcean 920MHz

Wearable

Mobile Health Care Security Big Data

Infrastructure Transportation Industry Medical Logistics Commercial BEMS HEMS Agriculture

RF

MCU

Sensing

NE

Ha

nd

bo

ok

［Overalltrends］ 2 Sensors covering our lives and social activity usher in a new era in information

［Applications/Thehumanbody］10 Medicine and healthcare beyond the five senses ［Applications/Vehicles］16 Supporting ADAS with diverse sensors ［Applications/Civilengineering］20 Sensor-driven infrastructure maintenance ［Applications/Architecture］26 Information technology saves energy in even small buildings ［Applications/Agriculture］30 Visualizing agricultural product status

［Newtrends/TrillionSensors］34 A trillion sensors create new businesses ［Newtrends/ IoT,IoE,andBigData］44 “Things” generating massive amounts of data ［Newtrends/Energyharvesting］46 From low-power to no-power ［Newtrends/Wirelessnetworks］50 Diverse techniques for each application ［Newtrends/ Infraredsensors］52 Applications expanding from automotive sector ［Newtrends/SmartMeters］54 Network control for household appliances, too ［Newtrends/MEMSsensors］55 Proving performance in consumer electronics ［Newtrends/CMOSsensors］56 The key to image data acquisition

contents

2

［Overall trends］

　Sensors and sensor utilization technologies are becoming increasingly important in a range of fields where electron-ics hasn’t been fundamental, such as automotive, medicine, construction, energy, and agriculture. 　Sensors have mostly been used for autonomous control of independent pieces of equipment, or system operation, such as factory automation（FA） systems automatically control-ling machine tools and other manufacturing equipment, or microwave ovens that monitor food temperature to cook automatically. In general, the ways sensors are used are de-veloping in two major directions（Fig.1）. 　The first is working to create new applications and new value by using increasingly sophisticated technology to ana-lyze and interpret the data collected by sensors. Sensors and

Sensors covering our lives and social activity usher in a new era in information

（1）Improved technologies for analyzing and interpreting data

Technologies combined with sensor technologyUtilization technology for microprocessors, FPGAs, etc.Digital signal processing technology

Application fieldsSelf-driving cars, non-contact and non-invasive medical tests, etc.

（2）Collecting and integrating large amounts of data to extract information

Technologies combined with sensor technologyRadio and other network technologiesInformation processing technology utilizing big data

Application fieldsMonitoring in construction, agriculture and livestock, and energy

Fig.1　Sensor utilization evolving in two directions

3

NE Handbook

autonomous control systems are evolving for expanded use in fields demanding safety and reliability, such as vehicle automatic braking functions, and medical electronics to con-tinually collect patient data.　The second is collecting and integrating the data from a large number of sensors with network technology, and extracting information useful in improving the quality of life or social activity. The maturation of “big data” thanks to new developments and applications in the information and communications technology（ICT） field is driving this trend. Sensors today are social devices, critical in the creation of sophisticated infrastructure. 　This report takes a closer look at sensor utilization trends as they develop in these two directions, and the evolving sensors that continue to make new applications possible.

New applications through developments in analysis and interpretation

　The technology to analyze and interpret data collected via sensors is evolving rapidly. 　Sensors can directly input physical quantities such as temperature, pressure, velocity, or brightness. Even the im-age sensor, one of the most advanced sensors, cannot sense a two-dimensional（2D） map of brightness distribution over an object. The only way to obtain information significant in controlling equipment, such as determining what an object is, or what state it is in, is to analyze and interpret collected data. 　Recognition technology, needed to extract information es-sential in equipment control from collected sensor data, has evolved enormously in recent years, thanks to rising perfor-mance and falling prices for the semiconductor devices used

4

Overall trends

for image processing, such as microprocessors, digital sig-nal processors（DSP）, and field-programmable gate arrays

（FPGA）. Another major factor is the continuing evolution of the algorithms used to efficiently analyze and interpret data. Here are a few representative examples. 　Right now, perhaps the most exciting field of technology development for vehicles is autonomous driving（pp.16-19）. Practical self-driving cars will have to be equipped with a di-verse variety of sensors, and engineers are already consider-ing image sensors, infrared sensors, millimeter wave radar, laser radar, and ultrasound sensors, among others. The au-tomatic braking function, positioned as a necessary prelimi-nary to autonomous driving, is already in commercial use, and became mandatory on all commercial vehicles in the

Fig.2　Sensor fusion application in driving

（a） Grasp position of vehicle two cars ahead using millimeter wave radar

（b） Dual single-lens cameras

Sensed vehicle Millimeter waves pass under first car

Lane sensing camera

High-beam control camera

millimeter wave radar

Alarm （audible, visual） and automatic braking

5

NE Handbook

European Union（EU） in 2013. Analysis and interpretation of imagery from around the vehicle provides information on positions and distances of nearby vehicles, pedestrians, and lane lines. 　Before automatic braking can be upgraded to full-fledged automatic driving, however, recognition precision must be improved. Automobile manufacturers and sensor manufac-turers both are working to improve sensor precision, and develop sensor fusion technologies to integrate multiple sensors（Fig.2）. The key to success here will be how to best utilize different types of sensors to implement a safe, low-cost autonomous driving capability.

Constant health monitoring

　In medicine, technologies used to analyze and interpret sensor data are being utilized to acquire biological data non-invasively, and even without physical contact.　Until recently, the biological information essential in medical diagnosis was usually obtained by restraining the patient, or attaching electrodes to the patient’s body, or by some other unpleasant method. No doubt many people have felt stress or nervousness when having their blood pressure or an electrocardiogram taken. 　With non-contact, non-invasive measurement, however, patients wouldn’t need to worry so much. The approach would combine accuracy with convenience, and has already been positioned as a key technology for constant health monitoring systems. Concretely, Fujitsu Laboratories Ltd. of Japan has developed a system to measure pulse rate and heart beat using an image sensor. Image processing technol-ogy analyzes facial colors from a video stream to detect the pulse.

6

Overall trends

Tapping into big data to expand application

　Another direction of growth is collecting and integrating data from sensors, and extracting information useful in im-proving the quality of life and social activity. 　Concepts like the Internet of Things（IoT）, big data, and machine-to-machine（M2M） are driving new information systems for the new era in the ICT field（pp.44-45）. By com-bining these information systems and sensor networks it is now possible to extract information from the massive volume of collected sensor data and illuminate previously invisible social activity. 　Google Corp. of the US created a bold new service with significant value by organizing the huge amount of infor-mation in virtual space. Sensors, big data, and IoT together will expand this revolution from virtual space into the real world. It is possible that godlike services could emerge, ca-pable of answering instantly such questions as “How many

Fig.3　The TSensors Summit（October 2013）

7

NE Handbook

people in the world are awake right now ?”　The organizations involved in developing sensor technol-ogy are steadily bringing this future closer. At the TSensors Summit in the US a project was launched to create the Tril-lion Sensors Universe, a company using sensor networks on the order of a trillion sensors a year（Fig.3, pp.34-43）. It will work on technology development and application for the supply and use of more sensors than ever tried before: a trillion sensors is about one hundred times more than the total annual sensor demand at present. Trillion Sensors plans to put sensors on all sorts of equipment and tools that have never had them, bringing about a world enjoying all the benefits of ICT. In short, it is a key technology for the realization of the Internet of Things.

Sensor networks as infrastructure

　In Japan as well, a national project is under way to use sensors to support society as high-level infrastructure: the Project to Develop Sensor Systems for Responding to Social Issues, launched by the Ministry of Economy, Trade and Industry（METI）. The project was consigned via the New Energy and Industrial Technology Development Organiza-tion （NEDO） to NMEMS technology research association of Japan. Development is under way now on sensor basic and application technologies. 　There are a large number of issues in Japan which de-mand a major overhaul of the infrastructure. In construction the social and industrial infrastructure suffers from a vari-ety of problems due to natural disaster and age（pp.20-25, pp.26-29）. Agriculture needs to improve safety and reliabil-ity of agricultural and livestock products, thereby improving international competitiveness（pp.30-33）. In medicine, soci-

8

Overall trends

ety faces skyrocketing medical costs brought on by a society of fewer children and an aging population. 　Social issues such as these involve huge scales, and com-plex systems of nature, plants and animals, and people, mak-ing it difficult to adequately grasp the causal phenomena. In order to fully comprehend a phenomenon, it is essential to collect information on diverse aspects of society. NMEMS has proposed a constant monitoring system for social issues, which would run continuously to help grasp involved phe-nomena and provide the needed information for decision-making. It is developing the necessary constituent technolo-gies now.

The impact of sensor evolution

　Much of the new sensor development in progress now is actually just new application technology for existing sen-sors. If new sensors are developed for new applications, of course, adoption will accelerate. 　A number of key areas have been identified as promising for new sensor development: finding ways to capture data currently unavailable, integrating information processing and communication functions, multi-module designs incor-porating functions from different types of sensors, arrays of sensors of a given type, and improved reliability and envi-ronmental resistance to make it possible to utilize them in as many situations as possible. 　An example of a sensor to capture information that was previously difficult to get would be the near infrared image sensor from Rohm Co., Ltd. of Japan, which is being devel-oped collaboratively with the National Institute of Advanced Industrial Science and Technology （AIST）, and will provide visualizations of the human body from the skin to a depth of

9

NE Handbook

a few cm（pp.10-15）. The sensor will be able to make can-cerous cells visible from outside the patient’s body. Blood flow can also be visualized, suggesting that it might be pos-sible some day to “read” emotions based on differences in blood flow caused by differing areas of activity in the brain. 　Technologies to integrate multiple sensors and peripheral circuits, to miniaturize sensors, and to improve reliability are also crucial. Emerging cloud technologies mean that data no longer has to be stored or processed where it is acquired. Instead, it can be processed by a central facility in a site designed for smooth operation of electronic systems. The information input functions of the sensors, on the other hand, must be located where the data is born, which means they must be environmentally tough, compact, power effi-cient, and low cost. 　Electronic systems consist of input, output, processing, storage, and communication. Of these, there has been ma-jor improvement in performance and function for output

（display technology）, processing（microprocessors and memory）, storage（memory, hard disk drives）, and com-munication（network technology）, but input continues to lag far behind. On the other hand, that same fact also means that the appearance of new sensor technologies could trig-ger enormous development in the utilization of information throughout society.

10

［Applications/The human body］

　Visualizing the formerly invisible portions of the human body, and slashing the cost of short- and long-term health care to monitoring lower the barriers for start-ups.　A number of exciting new proposals are being made in the medical and health care fields, a change from the semi-conductor and electronic component fields that have been popular of late. Semiconductor and electronic component manufacturers until recently have concentrated their efforts in consumer electronics, such as smartphones and personal computers, but now they are combining the high-reliability, low-cost technologies gained with newly developed tech-nologies to expand into non-consumer fields. 　The primary business of ROHM Co., Ltd. of Japan is semi-conductors, but the firm began expanding its scope of ap-plication beyond consumer electronics quite some time ago. Rohm Managing Director Hidemi Takasu, in charge of the R&D Headquarters, explains that development adopted the

Medicine and healthcare beyond the five senses

Fig.1　Vascular imaging with near infrared lightThe image on the left was taken with a CIGS image sensor, using 880nm near infrared illumination. Shots taken with 780 and 950 nm illumination were added to the image on the right, and images processed to show vessels distinctly. （Source: Rohm）

11

NE Handbook

Fig.2　Applications in biometric verificationThe visible light image is shown on the left, and the near infrared im-age at right. （Source: Rohm）

Visible Light Image NIR Image

Blood Vessel

motto “More than Moore” twenty years ago. Until recently the firm has primarily worked on expanding the range of product application while ignoring the restraints imposed by Moore’s Law on performance improvements in PC and server semiconductors.

Visualizing the human body and measuring stress with new materials

　For example, the firm is working on a semiconductor that offers optical and chemical properties superior to those found in silicon, a commonly used semiconductor material. This new material will enable the development of new medi-cal and biological sensors, and low-power monitoring ele-ments capable of operating for extremely long periods. 　The new material will be used in an X-ray imaging sen-sor with 10µm resolution, an imaging sensor capable of showing non-visible spectra from infrared to ultraviolet, and more. 　One image sensor can visualize the human body （Fig.1）,

12

Applications/The human body

Fig.3　Tiny fish bones captured by X-ray image sensorAn X-ray photograph of a fish made by the X-ray-sensitive image sensor developed by Rohm. （Source: Rohm）

High resolution image can be captured!

SOI Pixel（INTPIX4）Pixel Size : 17um×17umNo. of Pixel : 512×832

（= 425,984）Chip Size : 10.3mm×15.5mmVsensor=200V, 250us Int.×500

（=1/8s）X-ray Tube : Mo, 20kV, 5mA

using near infrared light with a wavelength longer than that of visible light. Near infrared can penetrate about 3cm into flesh, and in this system is emitted by a light-emitting diode

（LED） and reflected light detected by a custom imager us-ing a compound CIGS（copper indium gallium （di）selenide） membrane. By sensing different infrared frequencies sepa-rately for image processing, blood vessels and other features can be made to stand out（Fig.2）. 　If vessels can be visualized clearly, then it can be utilized in high-precision biometric verification. An application of Raman scattering with 1.2µm near infrared light can also identify cancerous cells clearly. 　In X-ray imaging technology, the new sensors will deliver scans that are clearer and more precise than existing X-ray systems（Fig.3）. An X-ray of a fish, for example, shows

13

NE Handbook

Fig.4　Blood tests with minute samplesThe blood sample is fed into the chip, and the chip placed into the equipment. Results are ready in about six minutes. （Source: Rohm）

bones as small as 10µm in size. The firm is currently devel-oping a system capable of detecting mammary cancer. 　Another development is a single-chip sensor that can digitize a variety of wavelengths. The chip incorporates sen-sors sensitive to light frequencies in the ultraviolet, visible, and infrared spectra. This spectrometer is implemented as a single semiconductor chip, and as a result will be small, low dissipation, and（in volume production） low cost. Research-ers have also developed a transceiver module for terahertz

（THz） radiation, which can pass thorough a variety of ma-terials with unique reflection characteristics. 　One type of low-dissipation semiconductors is the non-volatile device, which is off unless needed. 　In addition to medical devices, Rohm is also developing and selling medical equipment, including Banalyst（Fig.4）. A minute amount of blood is drawn from the subject, and in five or six minutes Banalyst outputs results for a number of key factors including HbA1c, CRP, and hsCRP. The device can also be used with saliva, and offers an objective, quan-titative measurement of stress level, which until now has been measured through verbal interaction.

14

Applications/The human body

Fig.5　Measuring stress via fingertip blood flowPulse rate is measured using the reflected green light. （Source: Rohm）

HemoglobinBlood vessel

Heart

Green LED Photo

Detector

What we can determinefrom the pulse wave

expansion/contraction

Variation ofblood stream

Hemoglobinabsorbs the light

1 pulse Pulse wave

Time

Light Attenuation

（absorption magnitude）

Attenuation byblood in vein

Attenuation byhuman tissue

Variation

Constant

Attenuation byblood in arteryAttenuation byblood in artery

　A method already exists to quantify stress and tension by measuring the amount of green light reflected by fin-gertip blood flow（Fig.5）. Green light is absorbed by blood hemoglobin, which means that reflection intensity varies with blood flow. Results can be used to measure pulse rate, stress, and tension, as well as assist in diagnosis of vessel aging and atherosclerosis.

New industries through expanded human senses

　“We are looking into ways of using these devices to ex-pand human senses, and create new industries,” continues Rohm’s Takasu. He suggests that it would be possible to sense information that human beings cannot, and feed that information back in a human-sensible form（Fig.6）. 　For example, new sensors can pick up light that human eyes cannot see, or sounds that human ears cannot hear, and make them sensible to human beings by directly stimu-lating the brain, or muscles. 　If user intentions or emotions can be input as data, then a variety of new applications become possible. “It might be

15

NE Handbook

Fig.6　Expanding human sensesSensors are used to expand the range of human senses by feeding information back in a way that can be sensed by human beings. This information could be used to actuate human function, such as by di-rect muscle stimulation. （Source: Rohm）

Sensing

Expanded sensing function

Actuation

Enhanced humanfunction

Five senses

possible to make a game, for example, that reads user inten-tions and develops a strategy to counter them,” he adds. 　Rohm is now developing customers for the new devices, preparing to launch business operations. In the past, Rohm’s customers have almost always been electronic equipment manufacturers, but this time they have expanded their scope to cover manufacturers of medical electronics, and health service providers. 　Instead of offering independent units, they are selling solutions. One proposal is a complete system, now being offered to long-term health care providers. The R&D Head-quarters has its own sales force to introduce new solutions to service providers.

16

［Applications/Vehicles］

　The acronym ADAS（Advanced Driving Assistance Sys-tem）refers to the entire array of systems such as automatic braking used in a “collision-free” car, and increasingly stringent regulations are accelerating ADAS adaption. The European safety standard for new cars, EuroNCAP, plans to include automatic braking and lane veer warning systems as evaluation items from 2014, and an automatic braking sys-tem with a pedestrian sensor from 2016. Automatic braking functions will become mandatory in Japan in large buses and trucks first, and the scope of coverage expanded gradu-ally into other classes, from November 2014.　There is a variety of vehicular obstacle sensors, includ-ing cameras, infrared sensors, millimeter wave radar, laser radar, and ultrasound（Table1）. At present, the most com-mon design combines a single-lens camera with millimeter wave radar, complementing the low-cost camera with radar

Supporting ADAS with diverse sensors

Table1　Major sensors used in autonomous driving（by Nik-

Performance Camera Infrared sensor Millimeter wave radar（76GHz）

Millimeter wave radar（79GHz）

Millimeter wave radar （24GHz）

Laser radar Ultrasound sensor

Range To about 40 m ○ ○ ○ ○ △ ○ ×To about 150 m ○ ○ ○ △ × ○ ×

Distance resolution（Under 30 cm） × × × ○ ○ ○ ×Angle detection ○ ○ × ○ ○ × △Relative speed detection × × ○ ○ ○ × ×Environmental resistance

Rain, snow, fog × ○ ○ ○ ○ × ×High temperature ○ × ○ ○ ○ ○ ○Low light, no light × ○ ○ ○ ○ ○ ○

Remarks Inexpensive single-lens cameras; high-performance stereocameras

Detects heat of people and animals even at night

Cost is drop-ping, but us-able waveband is narrow

Wider waveband from 2015 will improve detec-tion precision

In limited use in Europe and Japan

Good for 3D envi-ronmental sens-ing at short and medium ranges

Low-cost so-lution already used in many vehicles

17

NE Handbook

to provide good recognition precision even in rain, fog or other inclement weather, and at night. Low-cost cars such as compacts are more commonly being equipped with infrared laser radar. 　Manufacturers are extremely interested in sensor fusion, integrated control of multiple recognition sensors, as a nec-essary tool for realizing self-driving vehicles. Cameras are generally expected to assume the primary role.　“Nissan is really forging ahead,” became a common com-ment among ADAS engineers after September 2013, which was the date that Nissan Motor Co., Ltd. of Japan announced the new X-TRAIL at the 65th Frankfurt Motor Show（Inter-nationale Automobil-Ausstellung, or IAA）. 　The vehicle implements automatic braking with one single-lens camera, utilizing it to measure distance to ob-stacles in front of the vehicle. Distance is usually measured with millimeter wave radar or stereocameras, and a number of people in the industry have expressed apprehension con-cerning the precision available from a single-lens camera.

kei Electronics based on material courtesy Panasonic Corp.）

Performance Camera Infrared sensor Millimeter wave radar（76GHz）

Millimeter wave radar（79GHz）

Millimeter wave radar （24GHz）

Laser radar Ultrasound sensor

Range To about 40 m ○ ○ ○ ○ △ ○ ×To about 150 m ○ ○ ○ △ × ○ ×

Distance resolution（Under 30 cm） × × × ○ ○ ○ ×Angle detection ○ ○ × ○ ○ × △Relative speed detection × × ○ ○ ○ × ×Environmental resistance

Rain, snow, fog × ○ ○ ○ ○ × ×High temperature ○ × ○ ○ ○ ○ ○Low light, no light × ○ ○ ○ ○ ○ ○

Remarks Inexpensive single-lens cameras; high-performance stereocameras

Detects heat of people and animals even at night

Cost is drop-ping, but us-able waveband is narrow

Wider waveband from 2015 will improve detec-tion precision

In limited use in Europe and Japan

Good for 3D envi-ronmental sens-ing at short and medium ranges

Low-cost so-lution already used in many vehicles

18

Applications/Vehicles

Automatic driving with a single-lens camera

　The single-lens camera making it possible was developed by Mobileye of Israel. Other functions provided by Mobileye include warnings of other vehicles and pedestrians, and warnings of lane veering based on lane line sensing. In the new X-TRAIL, the firm has demonstrated that a single-lens camera can be used to implement automatic braking. 　The company has already prototyped a test car with au-tomatic driving based on one single-lens camera, in a move calculated to demonstrate the performance of the approach. The test car has been trialed on public roads in Israel exten-sively since 2012, and Mobileye is now developing a system utilizing multiple single-lens cameras, slated for completion in about summer 2014. 　There is no denying that some automobile manufactur-ers are uneasy about using only one single-lens camera. In response, the company explains it is working on “using mul-tiple single-lens cameras to improve recognition precision and provide redundancy.” Concretely, the already-developed single-lens camera with a 52° angle of vision will be used for intermediate distances, and an additional camera with a 26° angle of vision will handle distances over 200m. 　

Succession of stereocameras

　Stereocameras deliver better precision than single-lens cameras for obstacle recognition and distance estimation, but are more difficult to get full performance from. The leader in the field at present is Hitachi Automotive Systems, Ltd. of Japan, which makes the EyeSight system used by Fuji Heavy Industries Ltd. of Japan. The competition in stereo-cameras is set to intensify rapidly from 2014 through 2015,

19

NE Handbook

as companies like Robert Bosch GmbH of Germany and Continental AG of Germany release new stereocamera prod-ucts. Bosch has developed a design with only 12cm between the two cameras, trying to facilitate mounting on smaller frames. The product from Hitachi Automotive Systems mea-sures 35cm between cameras. 　Prices are dropping rapidly for the millimeter wave radar used in conjunction with cameras, too. A millimeter wave ra-dar system could cost more than 400,000 yen in 2000, but the price is likely to drop under 10,000 yen in 2015. The biggest change is the material used in high-frequency cir-cuits: while GaAs semiconductors were most common in the past, SiGe is becoming increasingly popular. In 2015, even less expensive Si will enter widespread use, and because the major foundries handle volume production under consign-ment, prices will plunge. 　In addition to the material, the wider millimeter wave bandwidth also plays a part. Millimeter wave radar utilizes the 76 to 77GHz waveband worldwide, but it has proven dif-ficult to achieve high resolution in pedestrian sensing with a bandwidth of only 0.5 to 1.0GHz. 　The International Telecommunication Union Radiocom-munications Sector（ITU-R） is expected to allow use of the band from 76 to 81GHz by vehicular radar in 2015. It should be possible to effectively detect pedestrians with mil-limeter wave radar with a bandwidth of more than 1GHz. 　3D laser radar is also attracting considerable attention in the industry. While primarily utilized in military applica-tions, development for vehicular use is accelerating. Bosch, for example, is said to be developing a “third sensor needed for automatic driving,” which probably refers to 3D laser radar.

20

［Applications/Civil engineering］

　There are innumerable bridges and roads in Japan built thirty to fifty years ago that are rapidly approaching the end of their service lives. Simultaneously, though, the engineers and technicians responsible for maintaining and repairing the infrastructure are also aging, and with the drop in the population overall, maintaining the infrastructure is becom-ing a major social issue. One possible solution being con-sidered is to automatically measure physical change with sensor networks, thereby monitoring trends. 　By monitoring the strain on a bridge during an earth-quake, or the displacement of its various components, it is possible to check how much has changed from normal state. Continuous monitoring of loading, and calculation of cumu-lative load, is handy for estimating when maintenance and repair will be needed, and invaluable in rapidly aging bridg-es. It is impossible to automate maintenance, but monitoring improves human work efficiency and speeds up decision making. Given the increasing scarcity of people to actually do the work, it has become indispensible in infrastructure maintenance. 　Examples of sensors being used for monitoring are be-coming common, with the Tokyo Gate Bridge one of the most well known in Japan. Sensors have been installed into a few other sites as well, such as the Shuto Expressway in Tokyo, and its Yokohane Line branch. The BRIMOS bridge monitoring solution from NTT Data Corp. of Japan was de-signed for this type of application, and was recently installed on the longest bridge in Southeast Asia, the Cân Thó Bridge

Sensor-driven infrastructure maintenance

21

NE Handbook

in Vietnam that collapsed once in 2007. 　But how is sensor-based infrastructure monitoring actu-ally implemented, and what can the acquired data actually be used for? While the specific monitoring sites and items will vary with the type of infrastructure, structure, and ma-terials, the Tokyo Gate Bridge provides a good example. It is a steel bridge, and so strain effects are quite from those in concrete bridges, and the methods of measurement differ as well. 　Sensors can be installed for continuous data logging, or sited specifically to acquire periodically, such as at weekly intervals. In both cases data is collected, analyzed later, and used to make informed decisions on maintenance and re-pair.

Status monitoring for main bridge section

　The Tokyo Gate Bridge measures 2.6km in total length, and sensors have been installed on the 800-meter long main

Fig.1　The Tokyo Gate Bridge is monitored for three major objectivesThe bridge was designed to meet height restrictions imposed by Haneda Airport, and width specifications imposed by the needs of passing ships, and as a result the center section is a single steel sheet. Displacement is monitored primarily at the junctures between the center section and bridge supports. （Source: Bureau of Port and Harbor, To-kyo Metropolitan Government）

Monitoring range is center section（about 800m）

Bridge safety assessment based on displacement and acceleration sensors

Temperature change and bridge elongation/shrink

Weight of passing traffic

22

Applications/Civil engineering

bridge section in the center to monitor strain, elongation/shrinkage, motion of joints linking the main section to the adjoining sections, and other items （Fig.1）. Total weight of passing traffic is measured using the weigh-in-motion tech-nique, and data used to calculate bridge roadway loading. And while not monitoring the bridge, meteorological sensors have also been installed for wind speed and other items. 　There are three primary objectives in monitoring, namely rapid determination of whether the bridge is safe or not af-ter an earthquake, daily status monitoring, and collection of data for maintenance and repair planning （Table1）.　The main bridge section was selected for monitoring be-cause of the construction parameters for the bridge overall, and the structure of that section. The Tokyo Gate Bridge is a part of the Tokyo Bay Waterfront Expressway, which con-nects Wakasu in Koto Ward with the manmade land outside the Chuo breakwater. It had to be built wide enough and

Table1　Outline of Tokyo Gate Bridge monitoring

Monitoring objective

Monitored items Description

Safety after earthquake

Displacement in non-visi-ble locations, damage

Monitor force exerted on dampers on top of the bridge supports, and the stays connecting the bridge members to the supports to deter-mine if the bridge has suffered any displacement or damage. Bridge safety assessment can be com-ple ted thir ty minutes a f ter the earthquake.

Daily man-agement

Temperature change in-s ide b r idge members a n d r e s u l t i n g b r i d g e member change（elonga-t i on de f o rma t ion） f o r comparison

Bridge members elongate/shrink in synch with temperature change. Member displacement is mea-sured and compared to tempera-ture, and if they are out of synch it indicates unexpected strain.

Preventive mainte-nance

Weighing passing traffic w i th we igh- in-mot ion technique, by measuring deformation.

Bridge members degrade under cumulative loading (weight), but the concrete correlat ion is un-known. As a result, maintenance priority is assigned to sites with higher loading.

23

NE Handbook

high enough that it would not interfere with ships using Tokyo Port. In addition, because it is quite close to Haneda Airport, it had a maximum height restriction. 　After considering design, strength, and cost, the center section was constructed as a single steel sheet. Displace-ment of the center section, therefore, was monitored at points where it connected with other structures such as bridge supports or adjacent bridge sections.

Detecting positional displacement with fiber sensors

　Concretely, monitoring for assessing safety after earth-quakes consists of measuring change in components sus-ceptible to earthquake damage, such as the dampers on top of the bridge supports, and the stays connecting the bridge to the supports （Fig.2）. Accelerometers using fiber sensors, and other sensors, measure displacement from the original position, and applied force, providing data useful in assess-ing component structural safety. It is possible to make the final decision on bridge safety within thirty minutes after an

Fig.2　Sensors, including accelerometers using optical fiber sensors, detect bridge component displacement

Accelerometer（elongation/shrinkage collision）

Accelerometer（support damage）

Accelerometer（regulator damage）

Accelerometer（stay damage）

24

Applications/Civil engineering

earthquake. 　Fiber sensors detect external change through the effect of vibration on light passing through the fiber. While electrical-ly operated sensors only last for a few years, fiber sensors are said to have service lives of almost twenty. And since it is sufficient to merely pass light through the fiber, the power sources can be located at the ends of the fiber, eliminating the need for a power source in the middle of a bridge span, for example. 　For regular bridge management, deformation and tem-perature are measured in the center section, and the corre-lation checked. The bridge elongates and shrinks slightly, in close synchronization with temperature change （Photo1）, and if they are out of synch it is clear that there is a problem somewhere, such as unexpected strain. Monitoring makes it possible to identify and fix these problems early. 　For maintenance, sensors measure the weight on the steel roadway plates, which transfer traffic weight to the bridge members and supports—in other words, the weight of passing traffic. Weight is measured using the weigh-in-mo-

Photo1　Graph of de-formation and tempera-ture in center bridge sectionIf they are out of synch it suggests unexpected load-ing.

25

NE Handbook

tion technique （Fig.3）, which determines weight from mea-sured deformation. The bridge suffers more damage under heavier loading, so cumulative loading is tracked as another parameter in maintenance. 　There are no established guides for how much damage is caused by how much loading, however, and for the time being the system is merely determining which sites experi-ence the heaviest loading, flagging them for maintenance priority. Since the Tokyo Gate Bridge feeds into Tokyo, it is heavily traveled by large trucks, and so heavy loads are less frequent in the passing lane.

Fig.3　Measured weight of passing trafficThe graph shows the number of vehicles of 20 tons or more each day, for the week starting on July 15, 2012. Traffic on July 16（Monday） is as low as on the weekend because it was a national holiday. Note that measurements will count multiple vehicles in close proximity to each other as a single vehicle.

1000

800

600

400

200

0

Harbor inside（toward Wakasu）

Num

ber

of v

ehic

les

of

20 t

ons

or m

ore

Num

ber

of v

ehic

les

of

20 t

ons

or m

ore

Travel laneJu

ly 1

5（Su

n.）

July

16（

Mon

.）Ju

ly 1

7（Tu

e.）

July

18（

Wed

.）Ju

ly 1

9（Th

ur.）

July

20（

Fri.）

July

21（

Sat.）

July

15（

Sun.）

July

16（

Mon

.）Ju

ly 1

7（Tu

e.）

July

18（

Wed

.）Ju

ly 1

9（Th

ur.）

July

20（

Fri.）

July

21（

Sat.）

July

15（

Sun.）

July

16（

Mon

.）Ju

ly 1

7（Tu

e.）

July

18（

Wed

.）Ju

ly 1

9（Th

ur.）

July

20（

Fri.）

July

21（

Sat.）

July

15（

Sun.）

July

16（

Mon

.）Ju

ly 1

7（Tu

e.）

July

18（

Wed

.）Ju

ly 1

9（Th

ur.）

July

20（

Fri.）

July

21（

Sat.）

1000

800

600

400

200

0

Passing lane

1000

800

600

400

200

0

Harbor outside（from Wakasu）

Num

ber

of v

ehic

les

of

20 t

ons

or m

ore

1000

800

600

400

200

0

■ 50～59t vehicles■ 40～49t vehicles■ 30～39t vehicles■ 20～29t vehicles

Num

ber

of v

ehic

les

of

20 t

ons

or m

ore

26

［Applications/Architecture ］

　Building Energy Management Systems （BEMS） easily adaptable to even small-scale buildings are attracting con-siderable attention in North America. These systems deliver the biggest improvements in large-scale structures, by con-trolling building power to boost energy efficiency, and that’s where they are being installed. It is more difficult to justify the investment into the required information technology （IT） in smaller buildings, however, and as a result the installation ratio is much lower. 　The BEMS offered by REGEN Energy Inc. of Canada, on the other hand, can be easily added to existing buildings by merely installing controllers, and it is rapidly gaining popu-larity in the small-scale building sector.

Information technology saves energy in even small buildings

Fig.1　The controller installed on individual pieces of equip-ment（Source: REGEN Energy）

27

NE Handbook

Installation complete in a day or two

　REGEN Energy’s BEMS is of extremely simple design, consisting of only the controller （Fig.1）. Each piece of equipment that needs power control, such as air conditioner or pump, is equipped with a controller. The controllers ex-change data and control the equipment to optimize overall building energy efficiency. 　The system does not require concentrators or other equip-ment to centrally manage information. Each controller works in unison with all the others, sharing information almost like a swarm of bees working together. And that’s what the com-pany calls it: swarm logic, or swarm energy management

（Fig.2）. 　The controllers have internal ZigBee wireless transceiver

Fig.2　Swarm logic, where controllers work cooperatively to boost energy efficiency（Source: REGEN Energy）

28

Applications/Architecture

modules, capable of communicating with each other over a range of 800m. A single controller can be installed in 20 to 40minutes, which means a whole building can be done in a day or two, unless it’s unduly large. Given that simplicity, 95% of customers are retrofitting existing buildings. There has been no simple solution for existing structures, and many owners are buying now to fill the need. 　The current controller has a response time of two min-utes, which is more than adequate for demand response （DR; the system providing incentives to reduce consumption, or imposing penalties on excess consumption, during peak loads）. The newer model released in September 2013 cut this to only one second. It handles high-speed DR and makes it possible to respond to price fluctuations in the electricity market in realtime.

Investment recovery in only 1〜2 years with DR participation

　Judging from installations in the US, REGEN Energy’s BEMS cuts peak power by 15% to 30% on average. Peak cut directly translates into a lower base rate from the electric power utility, and if customers participate in DR they may also receive incentives. The controllers support AutoDR, so users don’t have to take any other action at all: when a con-troller receives a DR signal it simply implements control as programed.　Because the system can be set up just by installing the controllers, says president and CEO Tim Angus, “The instal-lation cost is about a third that of conventional BEMS.” In most cases, that means the investment can be recovered in three or four years, and if cash incentives from the electric utility for demand response are included, it can pay off in

29

NE Handbook

only a year or two. 　

California launches AutoDR

　The three major electric utilities in California, US—Southern California Edison Corp. （SCE）, Pacific Gas and Electric Co.（PG&E）, and San Diego Gas and Electric Co.（SDG &E）—have already begun AutoDR service. In 2012, they announced that they would comply with the Open ADR 2.0 standard, and REGEN Energy BEMS sales are booming as a result. Some 80% of the firm’s customers are in California. 　REGEN Energy was established in 2005, with the first controller prototype completed in 2007, and trial installa-tions operating from 2008 to 2010. They began full scale sales in 2010.

Business opportunities in Japanese small-scale buildings

　“We have great hopes for the Japan market, where BEMS are not very common in small-scale buildings,” comments Angus. Electric power supplies are tight and there is strong demand for building energy management. Japan is especial-ly lagging when it comes to retrofitting older buildings, and there would seem to be plenty of opportunity for REGEN Energy’s BEMS.

30

［Applications/Agriculture］

　Both farmers and the Information and Communications Technology （ICT） industry are eagerly promoting the adoption of ICT in agriculture. Farmers want to boost their international competitiveness now that Japan is involved in Trans-Pacific Strategic Economic Partnership Agreement

（TPP） negotiations, and the ICT industry is looking for new markets. The government is pushing too, as part of its “Abe-nomics” growth strategy. 　Smart agriculture is attracting interest from all over. It boosts productivity by utilizing ICT in the form of big data, and sensor networks to monitor agricultural growth pro-cesses （Fig.1）. The scope of application is no longer limited to closed, managed plant factories, but spreads to include open fields, greenhouses, and more. Wireless sensor net-works offer low prices and high reliability, and now that ICT is being tapped for uses in sale and procurement as well, it offers a way for agriculture to improve revenue and profit-ability and establish itself as a new industry stretching from agricultural production to the consumer. 　Major Japanese ICT companies such as Fujitsu Ltd. and NEC Corp. are already active in the smart agro field, and multiple device manufacturers are working on sensors to measure field nutrients, for example. For the ICT and elec-tronics industries, this is one of the few markets they are still not dominant in.

Support from agricultural and communications ministries

　Smart agro is not being left to private enterprise, how-

Visualizing agricultural product status

31

NE Handbook

ever. The government has developed a number of strategies designed to promote the growth of farmers and the ICT in-dustry. 　The Abe government has positioned the national agricul-ture, forestry, and fisheries industries as growth industries. For example, agricultural and fisheries production value has been trending downwards from the 1990s, but the government wants to boost it toward 2020. Under the plan announced by the Ministry of Agriculture, Forestry and Fish-eries （MAFF）, the 11trillion yen production value for agri-culture and fisheries will be increased to 14trillion by 2020. Exports will also be increased, with rice and its processed products, for example, to jump from 13billion yen in 2012 to 60billion in 2020.

Fig.1　Example of agricultural sen-sor network prod-uct（Manufactured by Fujitsu.）

32

Applications/Agriculture

　The Ministry of Internal Affairs and Communications （MIC）, meanwhile, has positioned agricultural, forestry, and fisheries products （foodstuffs） as “resources indispensible for living,” along with ores, energy, water, and the infrastruc-ture, and intends to apply ICT to ensure reliable, continuing supplies. The use of sensor networks and big data will first turn agriculture into a knowledge industry, and eventually support the creation of an information network capable of supplying value-added foodstuffs. Agricultural, forestry, and fisheries data will be used to boost productivity and estab-lish a sales network to achieve higher sales prices, making it easier to turn a profit. MIC is also eager to create new de-mand for ICT products and services.

Just collecting data has no value

　Smart agro offers considerable merit for a number of parties, but there are several problems that will have to be resolved first. Director, vice president, and founder Hiroshi Shimamura of eLAB experience company of Japan, a consul-tant in sensor network application systems, presented a talk on connecting and visualizing agricultural crops at a next-gen sensor symposium on the potentials and problems of smart agro on September 25, 2013, organized by the Japan Society of Next Generation Sensor Technology. 　This firm markets agricultural sensor network systems. Farmers can install smart agro systems fairly easily, but growing quality crops demands more than merely collecting data and leveraging big data: knowledge is needed to inter-pret the data, and algorithms to feed the data results back into growth processes. Shimamura points out this is not a trivial process. 　He cited an example of a farmer whose lettuce produc-

33

NE Handbook

tion was below expectation. An analysis of the cultivation history showed that insufficient water had been supplied immediately after planting. This type of analysis can be done by an expert in plant physiology, but is unlikely to be found in farmers even if they are skilled at growing lettuce. Experience at lettuce cultivation is not always useful when it comes to analyzing cultivation histories.

Noticing problems from raw data

　He cited another example as well, this time of a farm with a reputation for tasty melons. The farmer would always put on swimwear when turning on the sprinklers in the greenhouse, so that he could feel the humidity on his skin. Sunlight and other factors can result in delicate humidity variations even within a single greenhouse, and he modified sprinkling appropriately to match. His decisions were based on intuition, and it was difficult to capture this intuition in growth algorithms. A variety of external support is essential. 　These problems represent business opportunities. In the former example, farmers utilizing plant physiology expertise can expect to produce lettuce superior to farmers relying on intuition and experience. If the abnormalities concealed in sensor data can be noticed and acted on by even “average” farmers lacking knowledge on plant physiology, it would have value. Shimamura explains that instead of merely help-ing farmers notice the problems, the service would gain value by offering teaching value as well. 　Many parties are interested in producing value from raw sensor data: the computer companies selling big data, the device companies handling the raw sensor data, the experi-enced farmers, and the corporations that understand all of their needs.

34

［New trends/Trillion Sensors］

　An American entrepreneur has called for the establish-ment of the Trillion Sensors Universe, utilizing a trillion or more sensors a year, and his vision is developing into an in-ternational initiative that is attracting industry and research institutions from Japan, America, and Europe. 　Today about ten billion sensors are used around the world every year, and a trillion would be one hundred times greater（Fig.1）. The proposal covers such detailed applica-tions as putting sensors on each every pill, and verifying that the patient takes it as prescribed. If realized, the Trillion Sensors Universe would produce data on everything, make it possible to analyze that data, and create a safer, more ef-ficient society than ever before.

From Silicon Valley to the World

　The proposal was made by American entrepreneur Janusz Bryzek, who resides in Silicon Valley. He has launched seven start-ups already, and raised them successfully to commer-cial concerns. They grew sufficiently to evolve into business divisions of companies like General Electric Co., Intel Corp., and Maxim Integrated Products Inc. 　He began conceptualizing the Trillion Sensor Universe idea in about 2012, gradually developing it as he received feedback on his ideas. He reached the conclusion that sen-sor networks of huge scale throughout society could resolve a number of global-scale social problems including energy, medicine, and famine. 　In preparation, he has begun working with leading high-

A trillion sensors create new businesses

35

NE Handbook

tech corporations and universities to make it possible to obtain diverse and inexpensive sensors that anyone can use easily. The roadmap has set the year 2023 as the target for realizing his vision. 　He began drawing up the roadmap in February 2014. TSensors Summit of the US, a tech start-up launched to sup-port his activities, is working with interested parties, namely several dozen engineers, managers, and researchers from corporations, universities, and research institutions in Ja-pan, Europe, and the US.　The roadmap classifies sensors for the proposed trillion into about ten categories, and will standardize the manufac-turing platform for each. In addition to sensors, the concept also encompasses peripheral technology such as wireless networks, energy harvesting devices, the Internet of Things

（IoT）, and the Internet of Everything（IoE）. According to

Fig.1　The roadmap is only the first stepActivities toward the realization of the Trillion Sensors Universe, primarily by TSensors Summit. The target date has been set for 2023.

1 trillion mark

2007

100trillion

2012 2017 2022 2027 2032 2037

Annual sensor shipments

Year

2013: Sensors in pills for new growth

Until 2013: Sharp growth for smartphones

10trillion

1trillion

100billion

10billion

1billion

100million

36

New trends/Trillion Sensors

Bryzek, standardization will reduce the time needed to es-tablish volume production technologies and significantly cut manufacturing cost.

Still only a concept, but a fascinating one

　“It’s just a concept with no means of implementation,” says one manager in the high-tech sector. “It’s just not pos-sible without the full array of constituent technologies, including peripheral devices and systems, in addition to sen-sors,” comments management at an American tech start-up. There are many people in the industry who feel the Trillion Sensor Universe initiative is hopeless. 　At the same time, though, there are also many engineers and managers who actively support Bryzek’s work, because without it the era of a trillion sensors will never come to pass. Apparently, they are not moved so deeply by the bold-ness of the concept itself. 　In the information and communication technology（ICT） world, in fact, it is not terribly unusual to find people who believe that sensor demand will surpass a trillion sensors. Instrument and device manufacturers like Hewlett-Packard Co., Intel Corp, Robert Bosch GmbH of Germany, and Texas Instruments Inc., among others. 　A number of people join Bryzek in believing that a wide range of sensor types can serve as “social devices” to help resolve social problems. Libelium Comunicaciones Distribui-das SL of Spain, involved in infrastructure sensor systems, cites a number of examples that could reach a trillion sen-sors.　Bryzek is merely trying to minimize the time it takes society to reach the trillion sensor universe. Based on his experiences launching firms in the sensor field, he believes

37

NE Handbook

that it takes twenty years to create a new sensor business, and a fundamental problem is the “chicken or the egg” issue: which comes first, widespread adoption or low price?　The roadmap was drawn up to accelerate the realization of the trillion sensor universe, and the idea is attracting more than just sensor manufacturers and users. The infor-mation technology industry is also intrigued, hoping to le-verage the massive flows of information from those sensors in new businesses.

99% from brand-new sensors

　The idea of spreading massive quantities of sensors every-where to collect data seems to be much the same as the pro-posal for Smart Dust made in the 1990s by the University of California, Berkley. And the Smart Dust concept is already partially implemented in the form of sensor networks for monitoring in farms, factories, and similar applications. 　The difference between the trillion sensor universe and existing sensor networks is the sheer quantity of sensor types, and of sensors. In a society using one hundred times more sensors than today, less than 1% of them would be ex-isting types. The remaining 99% would be new applications that do not yet exist, or which exist but are impractical for reasons such as high cost. 　Many of the presentations at the TSensors Summit held in the US in October 2013, and the Trillion Sensors Summit Japan 2014 held in Tokyo in February 2014 discussed ap-plications which have yet to achieve widespread adoption.

Pill sensors and throwaway image sensors

　The pill sensors mentioned above, used to detect whether a pill had been taken as per prescription, would react with

38

New trends/Trillion Sensors

the patient’s stomach acid and use chemical energy to emit an electrical signal, which would be picked up by a skin patch. The sensor itself would be the size of a grain of sand, and made of silicon. Mark Zdeblick, co-founder and chief

（a）

（b）

（c）

39

NE Handbook

technical officer （CTO） of developer Proteus Digital Health, Inc. of the US, says it would just be excreted once swallowed.　One proposal suggests that existing image sensors could be made much cheaper by eliminating the optical lens and

Fig.2　Sensors on pills and underwear（a）The sensor-equipped pills （inside the case to right） and the skin patch. （b）The Rambus image sensor can be used to make inexpen-sive, throwaway cameras that do not need lenses. （c）A wireless sen-sor that can be pasted on like a piece of tape, developed by the Uni-versity of California, San Diego. （d）A bra equipped with a pulse rate sensor, which automatically opens the front hooks only when the pulse rate exceeds a target value. Developed by Verygry Co., Ltd. of Japan. （e）A helmet that senses when an athlete has received a dangerous impact, developed by MC10 Inc. of the US. （Source: Photos b, c, d, and e from corporate and university data）

（d）

（e）

40

New trends/Trillion Sensors

making them disposable. A diffraction lattice would be formed on the surface of the complementary metal-oxide semiconductor （CMOS） sensor so that it only detects light from one direction. Distortion would be handled in signal processing. It would find use, for example, in smart card fa-cial recognition.　There is also a proposal for biosensors created in sheets that could just be taped to the body. Once prices drop suf-ficiently for throw-away use, applications would spread rap-idly.

Opportunities for new information businesses

　“One possible business model would be to give away shoes fitted with sensors, and make a profit off of the sensor information,” explains Bryzek. The appearance of the trillion sensor universe would accelerate this type of business in an era where massive amounts of sensor information are col-lected and widely utilized.　In the trillion sensor universe, sensor data will mean add-ed value for service industries, because as it becomes easier to utilize this data, it will also be easier to combine it with other data and produce information that consumers want. 　For example, the interpretation of the output from the temperature sensors used as air conditioning thermostats could vary depending on whether they were installed near the window or in the hall, and whether they were exposed to sunlight or not. If sunlight is coming in the window, that sensor would be warmer than the one in the hall. By com-bining output from multiple sensors, and other related data, it would be possible to generate information that has value to the user. 　Sensor information can also be stored, and user trends

41

NE Handbook

analyzed from the log to produce useful information in a variety of promising businesses. There is no value in the sensor-generated location data for a user, for example, but if information analysis indicates that the user likes coffee from a particular coffee shop chain, it becomes useful marketing information. In other words, the combination of large sets of data produces value. 　The medical field as well needs sensor data. Young, healthy individuals will eventually grow old and become patients. If biomedical data is sensed and stored from youth, it becomes possible to analyze trends that might lead to illness, and make reliable predictions. This would be very valuable information, and “could be used very effectively by the government and medical institutions,” explains Junichi Maekawa, of InfoCom Research, Inc. of Japan. 　A number of major electronics manufacturers are already researching possible medical and healthcare information services. They all use a wide range of sensors and analyze big data, as well as assuming the realization of IoT and IoE.

Accumulating annual demand for a billion sensors, for a decade

　The TSensors Roadmap, which spells out the strategy for the implementation of the trillion sensor universe, is aimed at sensors which can be expected to show demand of a bil-lion sensors a year, for ten years. Janusz Bryzek explains that the total will exceed a trillion by 2023. The roadmap does not include sensors which are likely to reach that tar-get on their own, such as the microphones and acceleration sensors in smartphones. 　First Bryzek’s organization will group multiple types of sensors into specific TApp platforms broken down by sensed

42

New trends/Trillion Sensors

data type, defining parameters for each. He selected chairs by February 2014 for about ten TApps from a list of appli-cants, and the project descriptions have been updated often since. The TApps include non-invasive health monitoring, artificial senses, environmental sensing, infrastructure sens-ing, and sensing for the food industry. 　The plan calls for individual chairs to document their roadmaps before the end of 2014, with the final specifica-tion spelling out the entire project to be issued in June 2015. The next step will be for TSensors Summit to provide services designed to accelerate industry related to the tril-lion sensors, such as assisting new sensor-related tech start-ups. It also plans to begin lobbying the US government for financial assistance, claiming that the manufacturing indus-try will mean new jobs.

Sensors for under US$0.13

　The key items that have to be defined for each TApp are the target price and the optimal manufacturing method, the objective being to slash manufacturing cost through stan-dardization.　Given current trends in sensor market scale, Bryzek ex-pects that the target price will not exceed “0.1% of gross domestic product.” World GDP in 2023 is estimated to be 130trillion US dollars, which means, he explains, that the limit on sensor unit cost is US$0.13. Similar economic fore-casts indicate a per-unit upper limit on sensor note systems, including networks and control circuits, of under US$1.00. Applications are not specified in either estimate.　A look back at the way sensors have spread in smart-phones makes the relationship between unit price reduction and production volume increase very clear. Bryzek believes

43

NE Handbook

that shipping such a large quantity of devices will signifi-cantly slash unit cost, and has reflected that belief into the roadmap.

44

［New trends/IoT, IoE, and Big Data］

　The Internet of Things （IoT） is the network created by all sorts of things connected via the Internet, specifically ev-erything other than personal computers, smartphones, and such information technology （IT） products. Many of the televisions and gaming systems sold recently already com-municate via the Internet, and now it is becoming possible for white goods, sensors, and all kinds of equipment and components to do the same. 　Internet connection makes it possible for computers and other equipment to check on status or the environment, or even operate other things or affect the environment remote-ly. Many sensor networks are based on the Internet, and are therefore included in the IoT.

IoE and M2M are in the Internet of Things, too

　The term “Internet of Everything” （IoE） is used in the same context as the IoT, while machine-to-machine （M2M） is a communication system linking two machines to each other, or a machine to a computer. Communication that is not implemented through the Internet, such as 1:1 com-munication that does not use an Internet Protocol （IP） ad-dress is also called M2M.

More precise analysis of big data

　IoT is assuming increasing importance now that a vari-ety of data related to things is appearing on the Internet, leading to increased demand for communications and data-crunching power, the expectation that the number of

“Things” generating massive amounts of data

45

NE Handbook

networked things will surpass the number of smartphones in the near future, the potential to increase the precision of big data analysis, and the birth of new services based on IoT data or analyzed data（Fig.1）. 　This development could bring a host of changes in ef-ficiency, safety, and security to diverse industries including medicine, the environment, transportation and distribution, industry, architecture, primary industry, and disaster re-sponse. 　The impact that IoT might have is actually far greater than merely an Internet connected to a variety of things. Intel Corp. of the US, for example, has defined it as a revolu-tion on a global scale, with innumerable devices seamlessly connected and managed intelligently and safely on the network, providing valuable services to people, devices, and systems by instantly converting data into useful information.

Fig.1　The Internet of Things continues to grow（Source: IDC data modified by Intel）

Estimated Internet-connected devices worldwide20000

18000

16000

14000

12000

10000

8000

6000

4000

2000

0

BI INTELLIGENCE

Wearables

Tablets

Smartphones

Personal Computers（Desktop And Notebook）

Personal Computers（Desktop And Notebook）

Smart TVs

2004 2005 2006 2007 2008 2009 2010 2011 2012 2013E 2014E 2015E 2016E 2017E 2018E

Dev

ices

wo

rldw

ide （

unit:

100

0）

Internet of things

46

［New trends/Energy harvesting］

　Energy harvesting （also known as energy scavenging） offers electricity generation in a variety of places. The prob-lem is that the available power is very small. The majority of the systems on the market only generate on the μW order per-unit, which is far from enough to run, for example, a smartphone.　But even though the generated energy is small, the market is being eyed eagerly by industry because of the convenience it offers. The biggest sales point of energy harvesting is that a system utilizing it won’t require battery replacements, wiring, or maintenance… in other words, it represents a switch from low-power design to no-power design （Fig.1）. The technology is beginning to turn up here and there as engineers search for ways to tap into this convenience. The Hoki Museum in the city of Chiba, Japan, for example, has installed an audio guidance system with switches powered by energy harvesting. Control signals are handled via wireless, eliminating the need for new switch wiring, too. For art museums, where exhibits are changed frequently, power cables and other wiring have been a long-running problem. Energy harvesting is cable-free.

Changing peripheral components

　The key elements of a representative energy harvest-ing system are（1）detect an energy source and generate electricity, （2）convert the harvested energy with a power supply circuit, and store it to capacitors or rechargeable bat-teries（3）use the stored energy to drive a microcontroller,

From low-power to no-power

47

NE Handbook

sensors, etc., and （4）transmit the sensed information via wireless to an external system. 　The idea of energy harvesting is not new, and it has been a research theme for many years. It is being implemented more of late because of evolution in the peripheral compo-nents needed to take full advantage of the generating devices

（functions 2 through 4 above）. In addition, more and more applications are being developed which can utilize them. 　These evolved peripherals include power circuits capable of efficiently utilizing the generated power, wireless inte-grated circuit（IC）transceivers, microcontrollers, sensors, and other components operating with extremely low power consumption. Until now, even though the energy could be harvested, it was consumed driving the peripherals with none left to implement the target function. Now that ICs are available offering high efficiency and low dissipation, energy harvesting has finally entered the stage of practical utiliza-tion.

Low-power wireless transceiver ICs

　Higher performance of the power circuit has an especially

Fig.1　Examples of battery-free switch-es

48

New trends/Energy harvesting

great impact, because the power circuit determines defines how much of the generated power can actually be used, and how much is wasted on loss. Power circuits now can effi-ciently recover even extremely low voltages.　Low-power wireless transceiver ICs have an equal effect, and one of the most important firms in the business when it comes to energy harvesting is tech start-up EnOcean GmbH of Germany. The EnOcean wireless standard designed for communication between devices runs on no more than a tenth the power of competing systems. As Frank Schmidt, chief technical officer（CTO） of the firm explains, “Control is exceedingly simple.” The wireless IC for the above-men-tioned switch and similar applications implements on/off control by sending three signals, each about 1ms in length, over a 30-ms period. 　The sensors used to measure temperature, humidity, and the like also operate on lower power. The brightness sensors used for lighting control, thanks to development for mobile phones, are also running on less and less power, as are the microcontrollers managing the energy harvesting circuit, sensor drive, and other operations. For microcontrollers, the key point is to keep dissipation low in standby, but with a sharp rise for operation. This type of intermittent operation is extremely common in wireless sensor network applica-tions, so standby current drain is crucial. 　R&D on generators is under way as well. The Georgia Institute of Technology of the US and others developed a technology for generating power from vibration, with a high output density of 31.3mW/cm2.

Wireless sensor networks in action

　Progress in low-power, high-efficiency peripheral circuits

49

NE Handbook

and generators has finally made energy harvesting a practi-cal technology, and applications are waiting. There is plenty of room in addition to light switches, especially for wireless sensor networks. Sensors only need to send data a few times an hour, so power consumption is low, and systems can operate on very low levels of generated power. The scope of application for battery-free, wireless systems is growing rapidly. One example is a temperature sensor network in remote forests. It is capable of detecting forest fires, and would help minimize damage. Given the potential damage a fire could cause, and the money spent on people and materi-als to control a fire, a wireless sensor network would more than pay for its own installation and maintenance.　Health monitoring of infrastructures is another applica-tion rising rapidly in prominence. Structures such as build-ings or bridges are equipped with sensors, and changes in status monitored, making it possible to detect sudden changes or estimate service life. The collected data is in-valuable in maintenance and parts replacement. Demand is also high in motors and engines, for example. Automobiles are webbed with wire harnesses needed to drive the sen-sors that monitor component status, and if the thermal or vibrational energy of the engine or motor could be used to power cable-free sensors, the number of required harnesses would drop dramatically. Life recorders would also benefit from the technology. Mounting sensors on livestock or even wild animals would not only provide location information, but also temperature, pulse rate, and other data. And if the power source were the heat energy of the animal, even bat-tery replacement could be eliminated.

50

［New trends/Wireless networks］

　A brief outline of major standards for short-haul wireless communication technologies. Different standards cover dif-ferent wavebands, communication speeds, and ranges, as well as a variety of topologies for terminal-hub connection, for example. Standards such as Wi-Fi, Bluetooth, and ZigBee are well-known in Japan, but there are many more, such as the ANT/ANT+ standard being utilized in sporting applica-tions primarily in North America, and the EnOcean standard used in wireless switches for lighting and air conditioning.

Diverse techniques for each application

Table 1　Network topology　（table by Nikkei Electronics based on material courtesy LAPIS

Name Standard Communi-cation protocol

Frequency （MHz）

Speed （bit/s）

Range （m）

Transmission/reception current （mA）

Transmis-sion power

（mW）

Topology Characteristics

Wi-Fi IEEE 802.11

Wi-Fi Alliance

5600、5200、2400

300M、54M、11M

100 300 30 P2P, star General applicability, only streaming protocol

Bluetooth IEEE 802.15.1

Bluetooth SIG

2400 24M、3M、1M

20 35 2.5、1、100 P2P, star Affinity with mobile phones, can transmit music

Bluetooth Low Energy

IEEE 802.15.1

Bluetooth SIG

2400 1M 20 15 1（10） P2P, star Low-power version of Bluetooth

ANT/ANT+ None（exclusive）

ANT+ Alliance

2400 1M 20 15 1 P2P, star, tree, mesh

For fitness and sports, primarily in North America

ZigBee IEEE 802.15.4

ZigBee Alliance

2400、902～928、868～870

250k 50 20 1 P2P, star, tree, mesh

Sensor networks

ZigBee Green Power

IEEE 802.15.4

ZigBee Alliance

2400 250k 50 20（？） 1 P2P, star, tree（?）, mesh（?）

Low-power version of ZigBee, for harvest communication

Special low-power wireless

IEEE 802.15.4

None 150～950 100k 700 25 20、1 P2P, star, tree, mesh

General applicability, individ-ual national standards, increasing deregulation

Z-Wave None（exclusive）

Z-Wave Alliance

779～956 100k、40k、9.6k

30 30 1 mesh Home networks

Wireless HART

IEEE 802.15.4

HART Alliance

2400 250k 50 20 1 mesh, star, mesh+star

Specialized for industrial use

EnOcean ISO/IEC 14543-3-10

EnOcean Alliance

315、868、902、928.35

125k 100 25 1 star Specialized for harvest communication

51

NE Handbook

Name Standard Communi-cation protocol

Frequency （MHz）

Speed （bit/s）

Range （m）

Transmission/reception current （mA）

Transmis-sion power

（mW）

Topology Characteristics

Wi-Fi IEEE 802.11

Wi-Fi Alliance

5600、5200、2400

300M、54M、11M

100 300 30 P2P, star General applicability, only streaming protocol

Bluetooth IEEE 802.15.1

Bluetooth SIG

2400 24M、3M、1M

20 35 2.5、1、100 P2P, star Affinity with mobile phones, can transmit music

Bluetooth Low Energy

IEEE 802.15.1

Bluetooth SIG

2400 1M 20 15 1（10） P2P, star Low-power version of Bluetooth

ANT/ANT+ None（exclusive）

ANT+ Alliance

2400 1M 20 15 1 P2P, star, tree, mesh

For fitness and sports, primarily in North America

ZigBee IEEE 802.15.4

ZigBee Alliance

2400、902～928、868～870

250k 50 20 1 P2P, star, tree, mesh

Sensor networks

ZigBee Green Power

IEEE 802.15.4

ZigBee Alliance

2400 250k 50 20（？） 1 P2P, star, tree（?）, mesh（?）

Low-power version of ZigBee, for harvest communication

Special low-power wireless

IEEE 802.15.4

None 150～950 100k 700 25 20、1 P2P, star, tree, mesh

General applicability, individ-ual national standards, increasing deregulation

Z-Wave None（exclusive）

Z-Wave Alliance

779～956 100k、40k、9.6k

30 30 1 mesh Home networks

Wireless HART

IEEE 802.15.4

HART Alliance

2400 250k 50 20 1 mesh, star, mesh+star

Specialized for industrial use

EnOcean ISO/IEC 14543-3-10

EnOcean Alliance

315、868、902、928.35

125k 100 25 1 star Specialized for harvest communication

Semiconductor）　 （?） indicates uncertainty

Fig.1　Network topology

P2P

tree

star

mesh

device

hub

hub

device device

device

device

device

device

device

device

device

device

device

device

device

devicedevice

device

device

hub

hub

device

52

［New trends/Infrared sensors］

　The range of applications for infrared sensing is growing rapidly from the original thermography uses. It is emerging as a key technology in safety, with applications in identify-ing biologically contaminated meat cuts, identifying pills of the same color and shape, diagnosing cancerous cells and vein positions from outside the body, detecting people in healthcare and security uses, sensing alcohol in vehicle operator exhalations, as night vision systems for driving, de-tecting gas leaks, locating loose tiles on structure walls, and more. Automotive night vision systems, once limited to only high-end automobiles, are now spreading to a wide variety of vehicles, and special legal measures promoting their use are expected to come into effect in Europe in 2016-18. Parts manufacturers in the lens and semiconductor industries are getting involved, and the prices of cameras are ready to drop. 　Infrared light has a wavelength longer than that of visible light, but shorter than sub-millimeter wave radio. Character-istics vary with wavelength, and infrared is generally broken down into far, middle, and near infrared ranges. In sensing applications, the specific characteristics of each waveband are utilized. Applications for near and far infrared common-ly detect infrared radiation that is reflected or emitted by the target, while middle infrared can detect which infrared wavelengths are absorbed. Near infrared has the shortest wavelength, and is utilized in household appliance remotes, and IrDA and other infrared communication, as well as in sensing applications including night vision systems and infrared cameras. Near infrared light has reflection charac-

Applications expanding from automotive sector

53

NE Handbook

teristics similar to those of visible light, and can reach farther, while re-maining invisible to the human eye and there-fore unlikely to be no-ticed. The waveband is from 0.7 to 2.5µm. 　The infrared light with the longest wavelength is far in-frared, with a waveband of 4µm to 1mm. It is often used in thermography （temperature measurement）. Objects generally emit electromagnetic radiation if they are above absolute zero, and the emitted wavelength will vary with the temperature of the object. The most commonly measured objects have temperatures between minus tens of degree to plus hundreds of degrees （Celsius）, representing an electro-magnetic radiation wavelength peak from 3 to 20µm. 　Infrared wavelengths have a frequency of 300GHz at the lowest, which means they pass through cloth, paper and similar materials: a characteristic useful in determining the content of an envelope without opening it, for example. Auto-motive night vision systems also use infrared sensors. Autoliv Inc. of Sweden, which holds the overwhelming share of the market, uses a combination of near and far infrared sensors. 　Middle infrared has a wavelength between the other two, ranging from 2.5 to 4µm. It makes use of the fact that ob-jects irradiated by electromagnetic radiation will absorb a specific wavelength, a phenomenon frequently used to iden-tify materials. The absorption spectrum covered by middle infrared includes bases found in organic compounds（O-H, etc.）, and absorption spectrum characteristics can be used to identify chemical reactions.

Fig.1 　Imagery from a far infra-red image sensor（Source: Autoliv）

54

Fig.1　The smart meter network

Route A Route BElectric power utility

Smart meter

Solar panel

Storage battery

Household appliances

Electric vehicle

HEMS

［New trends/Smart Meters］

　Smart meters are systems incorporating multi-function watt-hour meters with equipment management functions, communication functions and more. 　By equipping watt-hour meters with short-haul wireless communication functions operable over ranges of a couple dozen to about one hundred meters, it becomes possible to connect them to facilities and equipment in the home or office such as air conditioners, lighting, thermostats and se-curity systems. The operational status of this end-user equip-ment is managed by the electric power utility via the net-work and the smart meter. In other words, the smart meter plays a key role in the smart grid, helping balance demand-side and supply-side system operational states to match the changing electric power supply-and-demand situation.　The reason behind connecting the watt-hour meter to equipment in the home is to manage energy use by these home systems. The first step is to make the home energy use status visible, showing the user the current situation and promoting an interest in saving energy. In the future, the electric power utility may be able to control air conditioner thermostats via the network for fine-grain energy saving measures on a society-wide scale.

Network control for household appliances, too

55

NE Handbook

［New trends/MEMS sensors］

　Many conventional sensors made use of material proper-ties, such as the piezoelectric devices converting deforma-tion into voltage. Microelectromechanical systems （MEMS） sensors, however, are tiny machines made with semiconduc-tor microfabrication technology. Tiny mechanisms, such as pendulums for example, react to external change, and that reaction is converted into a change in voltage or current. Compared to conventional sensors, MEMS sensors have few drawbacks, are easy to use, and boast excellent possibili-ties when it comes to future capabilities. MEMS sensors are made utilizing the precision film growth, photolith and etch-ing processes developed for semiconductor device manufac-ture, which enable the construction of mechanisms on the micrometer order. And in general the smaller the geometry, the better the sensitivity and precision. It is also fairly simple to single-chip the sensor device with the electric circuitry needed to process the signals, shortening the wiring be-tween the two to minimize external noise effects. It is also simple to combine multiple sensor devices with differing characteristics to detect a wider range of targets, or to make a sensor array to acquire distributed information.　The use of MEMS sensors in consumer equipment is ac-celerating sharply. Acceleration sensors, for example, have shown up in the controller for the Wii game system from Nintendo, while gyro sensors help correct hand wobble in digital cameras and silicon microphones are common in notebook PCs. Next-generation applications such as gas sen-sors and biological sensors are in the laboratory now.

Proving performance in consumer electronics

56

［New trends/CMOS sensors］

　Complementary metal-oxide semiconductor （CMOS） sen-sors are imaging devices that convert the charges stored in photodiodes into voltage, on a per-pixel basis, amplify the voltages and read them out. Together with charge-coupled devices（CCD）, CMOS sensors are the most commonly used types of solid-type imagers. Originally application was lim-ited due to excessive noise, but the development of CMOS sensors accelerated abruptly for use in mobile phones be-cause they can be designed for low power operation and miniaturized relatively easily. Advances in digital signal pro-cessing have led to improvements in noise compensation, eliminating that initial drawback. 　The difference between CMOS and CCD imagers in terms of structure is basically how the image signal is read. In both designs incident light is first converted to electricity by the photodiode, and the resulting stored charge is read as volt-age, then amplified for output. The CMOS sensor converts and amplifies these charges on a per-pixel basis, while the CCD sensor transfers charges through a “bucket relay,” and processes them all in the output stage.　The major problem with CMOS sensors is that because amplification is implemented on per-pixel basis, the amplifi-er threshold voltage varies, which can cause noise. Formerly CMOS sensors also exhibited high dark current, caused by lattice defects, but this has been improved significantly of late. New back-side illumination sensors have also been de-veloped, moving the metallization from above the diodes to below them, boosting sensitivity.

The key to image data acquisition

NE Handbook series　Sensor Networks

Publisher Nikkei Business Publications, Inc. 1-17-3 Shirokane, Minato-ku, Tokyo 108+8646 Japan Published June, 2014 Editor Nikkei Electronics Editorial assistance Nikkei Technology Online, Nikkei BP Cleantech Institute Motoaki Ito（Enlight, Inc.） Design Nikkei BP Consulting Printing Dai Nippon Printing

Sponsored by ROHM ©Nikkei Business Publications, Inc. 2014 All rights reserved. Printed in Japan