PhD Defense: Enabling Smart Homes Using Web Technologies

Enabling Smart Homes Using Web Technologies

Andreas Kamilaris

PhD Defense

Professor: Andreas Pitsillides

NETworks Research LaboratoryDepartment of Computer Science

University of Cyprus

December 2012

University of CyprusGeneral Overview

1. Introduction - Problem Statement - Motivation2. Building an Application Framework for Smart Homes3. Web-Enabling Home Devices4. Using Request Queues for Enhanced Performance5. Technical Evaluation6. Blending Smart Homes with Online Social Networking7. Integrating Smart Homes to the Smart Grid8. Beyond the Smart Home Environment9. Conclusion10. Future Work

University of CyprusIntroduction

• Merging of computing with physical objects.• Physical devices becoming smarter.• Home appliances equipped with embedded microprocessors, wireless

transceivers, sensors and actuators.• New automation possibilities in smart homes.• Technology disappears in the background of residents’ lives.

University of CyprusProblem Statement

• In an idealized vision of a fully integrated smart home, all the operations are efficiently controlled by a central application.

• Proliferation of incompatible standards/protocols used by hardware/software manufacturers.

• The smooth integration of appliances from different vendors becomes a very complex process.

University of CyprusMotivation: Internet of Things

• The Internet penetrates in embedded computing.• The Internet of Things envisions a network of objects, where all

things are uniquely and universally addressable, identified and managed by computers in the same way humans can.


Matthias Kovatsch et al., Embedding Internet Technology for Home Automation, in Proceedings of ETFA, Bilbao, Spain, September 2010.

“Internet technology, utilizing IPv6, will become the future standard in home automation.”

Carles Gomez and Josep Paradells. Wireless home automation networks: A survey of architectures and technologies. IEEE Communications Magazine, 48(6):92{101, 2010.

X10 KNX ZigBee IPv6

Network Size: 2^8 2^16 2^16 2^64 per subnet

Data Rate: 20b/s 9.6kb/s 20-250kb/s 250kb/s...1Gb/s

Interface: custom solutions

app-level gateway

app-level gateway

UDP, TCP, RESTful Web

Cost: low high medium low

Installation Overhead: low high low low

Connectivity: low medium medium high

Security: none high medium medium

Motivation

University of CyprusMotivation: Web of Things

• Interconnecting embedded devices in application level.• The Web of Things reuses Web principles to interconnect

embedded devices, built into smart things.• The Web as a pervasive and scalable platform.

The WoT practice:1. Connect embedded devices to the Internet,

via IPv4 or IPv6.2. Embed Web servers on the devices.3. Model their services in a resource-oriented way (REST).


REST is a lightweight architectural style which defines how to properly use the HTTP protocol as an application interface.

A Resource-oriented Architecture is about four concepts:1. Resources.2. Their names (URIs).3. The links between them.4. Their representations (HTML, JSON, XML).

Resources can be manipulated with:1. GET to retrieve a representation of a resource.2. POST represents an insert or update.3. PUT to alter the state of a resource.4. DELETE to delete resources.

REST Vs Big Web Services (WS-*)

Motivation: REST

University of CyprusThesis Objective

Investigate the feasibility of enabling truly

Web-based smart homes, following

the principles of the Web of Things,

for achieving interoperability,

flexibility and acceptable

performance in home environments.



University of CyprusRequirements for Future Smart Homes

• Support various interaction types (Ad hoc, pull, push).• Uniform access to heterogeneous home devices.• Multi-hop wireless communication, plug and play functionality.• Reliable operation, masking transmission failures.

• Flexible design, light implementation. • Direct access for residents to their home environment.• Concurrent, multi-resident support.• Interoperable programming interfaces for end user

development of smart home applications.• Graphical user interfaces.• Small waiting times for simultaneous requests.• Acceptable performance in terms of response times and battery

lifetime of devices.• Scalability.

University of CyprusEmbedded Devices in the Smart Home

I. Sensor Motes

• Telosb sensor motes.• Equipped with a 250kbps, 2.4GHz, IEEE 802.15.4-compliant

Chipcon CC2420 Radio, integrated on-board antenna and a 8MHz TI MSP430 microcontroller with 10 kB RAM.

• Equipped with temperature, humidity and light sensors.• Form a wireless sensor network inside the smart home.

University of CyprusEmbedded Devices in the Smart Home

II. Smart Power Outlets

• Ploggs• Firmware based on the ZigBee protocol.• Forming a mesh metering network.• High accuracy of electricity measurements.• Control of an electrical appliance remotely (switch it on/off).• External transducers for whole-home measurements.

University of CyprusBuilding an Application Framework for Smart Homes

University of CyprusBuilding an Application Framework for Smart Homes

• Synchronous/Asynchronous Operation


• A Web cache is an intermediary between Web servers and clients, monitoring incoming requests and saving copies of the responses for itself.

• Works only for GET requests using the expiration model for determining freshness of resources.

Building a Web-based Smart Home

Gateway Web Cache

(Web server)(Web client) (Web cache)


HomeWeb Client Application

Restlet-GWT

Restlet

Web API

Server Application Framework

XML JSON


• Adding a Graphical User Interface

University of CyprusBuilding a Web-based Smart Home


• Energy Awareness through a Web Interface

• Device-level energy consumption information.• Historical comparison with previous days, weeks, months, years.• Association of electricity data with costs.



• Smart Rules for Home Automation

If the illumination in the living room is less than 50% and the temperature in the kitchen is greater than 25 degrees Celsius, then turn on the red led of sensor7 and the green led of sensor6.



• Smart Rules for Energy Efficiency

“If the illumination in the living room is less than 20%, then turn off the television and the DVD player.”



function check { if [ $? -gt 24 ] ; then curl -d "status=OFF" -X PUT [serverAddress]/AirConditioner/Switch/ fi}curl -s -X GET [serverAddress]/Kitchen/Temperature/ $1check;

• Web mashups are Web resources that include content and application functionality through composition of existing resources.

• Physical mashups exploit real-world Web services, offered by physical devices, combining them using the same tools and techniques of Web mashups.



function getHttpRequest() { var xmlhttp = null; xmlhttp.open('GET', 'http:// [serverAddress]/ /touchatag/tags', true);

xmlhttp.onreadystatechange = function() { if(xmlhttp.readyState == 4 && xmlhttp.status == 200) { var items = eval('(' + xmlhttp.responseText + ')'); var secret_key = "04:BA:4A:B9:23:25:80"; for (var i=0; i<items.length; i = i + 1) { if (items[i].t == secret_key) $('locked').innerHTML = "Door is unlocked!"; } if (!unlocked) $('locked').innerHTML = "Door still locked."; } } xmlhttp.send(null);}


University of CyprusBuilding a Web-based Smart Home

Urban mashups, defined as opportunistic physical mashups, validated when the local environmental conditions support the sensor-based Web services, defined by the mashups.


• Automatic reasoning and advanced knowledge inference about environmental conditions.


Back



University of CyprusWeb-enabling Sensor Devices

1. Local Device Discovery• Multicast Discovery Protocol.• Transmit a single URL instead of a SOAP/XML payload.

Similar to WS-Discovery for WS-*.

University of CyprusWeb-enabling Sensor Devices

2. Service Description• Web Applications Description Language (WADL).• An XML-based language that provides a machine-

readable description of HTTP-based applications.

Similar to WSDL for WS-*.

University of CyprusWeb-enabling Sensor Devices3. Request-Response Interaction

• Each device an embedded Web server, offering sensor and actuation services through a RESTful interface.

• All interactions are done via standard HTTP calls.• IPv6-based WSN of Telosb sensor motes (6LoWPAN).• Based on blip in TinyOS 2.x• Indirect Web-enablement of Ploggs.

Resource URI Parameters REST Method Return Value

Temperature: - GET text/plain

Humidity: - GET text/plain

Illumination: - GET text/plain

Leds: Color (Red, Green, Blue) PUT Ack

Electricity: - GET JSON

Switch: Status (On, Off) PUT Ack


Connecting Ploggs to EnergieVisible

• EnergieVisible plots sensor data in real-time.• Pointed EnergieVisible to our application framework, by

feeding it with measurements from Ploggs in JSON format.

Web-enabling Sensor Devices


4. Web Messaging for Event-driven Scenarios• Pull Vs Push.• Client-server model not appropriate for event-driven scenarios.• RESTful Message System (RMS) is a push-based, lightweight publish/subscribe messaging framework, suitable for embedded devices.• A RESTful API on sensor motes, for managing subscriptions.



5. Device and Service Sharing• Can be achieved by harnessing social networking sites.



6. Other Issues• Global Web discovery of devices/services.• Security of devices against misuse.• Privacy of owners and users of the devices.• Semantics of sensor information.




University of CyprusUsing Request Queues

• Transmission failures happen in indoor environments.• Home devices have battery limitations and frequent failures.• No guarantees. High unpredictability.

• Better management of the interactions with embedded devices.• Reliability and performance need to be ensured.

• Request queues a suitable intermediate data structure for enhancing the performance of pervasive applications that target smart homes.


• Request queues are defined as FIFO queues.• Installed on middleware applications for smart homes.• Handle the requests coming from the home’s tenants,

targeting the embedded devices of the house.

Using Request Queues

University of CyprusRequest Queue Operation

University of CyprusRequest Queue Analysis

• Incoming requests need to wait in the queue for their turn, in order to be executed.

• Waiting time at the queue is a considerable amount of time in increased workload.

University of CyprusExperimental Setup• 6LoWPAN-enabled Telosb sensor motes.• Sensing capabilities exposed as RESTful Web services.• Transmission power at -25 dBm, message sizes 128 bytes.


• Request queue retransmission interval α

Average RTT

St. Deviation


• Influence of transmission failures and different arrival rates on retransmission interval α.


• Influence of varied response times on retransmission interval α.

• RTT times and St. Deviation values learned from the device thread. • Set initially to a larger value, leaving a "safe margin”.• Fine-tune adaptively during the device operation.

University of CyprusPotential Benefits of Request Queues

• Multi-Client Support

• Multi-hop topology additional delays of around 200 ms.• Heavy workload increases response times by 18-20% in the single-

hop case and 14-17% in the multi-hop topology.


• Avoiding Transmission Failures

• In light workload, transmission failures do not affect significantly the response times.

• In heavy workloads, transmission failures cause the response times to grow almost exponentially.

Potential Benefits of Request Queues


• Estimating Potential Response Times

• Average estimation error is 12.38%, and it increases to 14.60% when the request queue size becomes larger than 2.



• Load Balancing for Serving High Traffic

• In low traffic, the improvement of performance is around 4-6%.• In increased traffic, the improvement reaches 11%.


1. Whenever a new request appears for a service, estimate the potential response time for every device that offers service.

2: Forward the request to the embedded device that offers the least estimated response time.


• Handling Priorities

1. Assign a priority to each request (low, normal or high).

2. Each prioritized request is translated into an integer value by the application framework, according to the following formula: low=1, normal=5 and high=10.

3. The priority heap selects for execution the request with the highest priority number.

4. To avoid starvation of low-priority requests, the priorities of all waiting requests are increased by 1 at every round, i.e. at a successful execution of some request.




University of CyprusTechnical Evaluation

Performance Metrics

• Average Request/Response Time (ms)• Energy Consumption (J)• Cache Hits (%)


A scenario of a family with many members

• Multiple family members interact with their home devices through the Web.

• Home residents modeled as software agents.• Each agent assigned a unique TCP socket.• Agents select randomly devices/services.• The arrival rate lambda of family members is modelled by

the exponential distribution.• Five minutes simulation time.

University of CyprusExperimental Setup

A single-hop Topology A multi-hop Topology

• A single-hop topology does not cover a typical smart home.• The indoor range of a typical sensor mote is 20-30 m.• A multi-hop 2-3-4 tree topology. 4 leaf IPv6-enabled sensors.


A multi-hop TopologyA single-hop Topology

• Simulated REST Vs 6LoWPAN REST.• Simulated REST message sizes 80 bytes.• The effect of Web caching.


• Web Caching

• Increase is higher between 10-25 seconds of freshness time.• Cache hits reach 90% with freshness time around a minute.


• Web Caching

• Small increases in freshness time reduce the request time linearly with a large gradient.

• At freshness time of 60 seconds response time only 100 ms.


• Energy Consumption Performance

• Avrora Simulator for AVR microcontrollers.• Energy consumption of the leaf nodes in the multi-hop 2-3-4

topology of IPv6-enabled sensor motes.

Bigger energy consumption due to the 6LoWPAN packet overhead


• Event Handling

• Push Vs Pull Web Messaging• A fall in illumination levels once every five minutes.• Pull frequency 30 seconds.

23% less energy consumed in Push messaging



University of CyprusSmart Homes and Online Social Networking

• Two thirds of global Internet Population visit Social Networking Sites (SNS).

• Facebook has more than one billion active users!

Social networking has become a fundamental

part of the global online experience.

The Web 2.0 is a social Web!


• Sharing Home Devices through Online Social Networking

Smart Homes and Online Social Networking


• A Pub/Sub Mechanism with Facebook Notifications



• A social competition between neighbouring flats towards efficient energy utilization.

• Exploring entertainment through a social game and the social influence of the neighbourhood, as parameters for energy conservation.

• The influence of the community has the potential to drive residents towards a persistent behavioural change.



• Social Norms

“People tend to follow what other people do and adapt their behaviour and practices according to the stimuli received by their friends, relatives and neighbours”.

“Social norms can motivate people to question their attitude, if they discover it is not ”normal”.


• Rules and Conditions

• The competition would take place in blocks of flats.• The duration of the competition is one month.• Daily feedback about each flat’s and the whole block’s

consumption, flat ranking in the competition.• Feedback through a website, a Facebook application and a

notice box located at the main lobby.• The winning flat is the flat reducing most effectively its

electrical consumption.• Comparison with electricity bills from previous months.• The award to the winning flat would be an energy monitor.



Plogg Smart Power Outlet

Flats’ Residents

Microsoft SQL Server database

Web Server

Flat Mains Meter



Suburb Urban

Flats: 10 20

Participating Flats: 6 20

Residents: 10 29

Age 18-25: 2 10

Age 26-35: 6 12

Age 36-45: 2 4

Age 46-55: - 3

Age 56+: - -

• Case study: Two blocks of flats


Suburban Block of Flats Urban Block of Flats

• Comparing with previous months, 11.90% average reduction of energy in the suburban case and 27.74% for the urban block.• Average energy savings in the urban case are 2.4x more.• In the urban block, an increase of temperature by 2 degrees Celsius.


University of CyprusSuburban Vs Urban Block

• Strong correlation of daily temperature to block’s energy consumption.• People at the suburban block consumed in average 11% more energy.• Residents at the urban block mostly highly educated students.• Demographic analysis based on age, sex, yearly income and number

residents per flat.

Suburban Block Urban Block

University of CyprusDemographic Analysis: Age

• Older people consume more electricity, as they spend most of their time at home.

• Age groups 26-35 and 46-55 are mostly influenced by the competition, reducing their consumption by 32%.

• It may be more convenient for people that spend much time at home, to observe and analyze their consumption, taking countermeasures.

University of CyprusDemographics Analysis: Sex

• Females tend to consume more electricity as they (usually) spend more time at home, having energy-demanding habits.

• Women have contributed more in saving energy, reaching 30% reductions, while men around 20%.

• In general, females were more interested in the competition. They found the perspective of protecting the environment appealing.

University of CyprusDemographic Analysis: Yearly Income

• Tenants with high income consumed more energy as they were not willing to sacrifice their comfort just for saving money.

• Residents with low income consumed less than half the energy of their high-income neighbours.

• Low-income residents had the least savings, as they probably had already tried to save energy in the past, to reduce their costs.

• High-income residents reduced their consumption by 30%, motivated because of environmental reasons and not to save money.

University of CyprusDemographic Analysis: Residents per Flat

• More tenants at each flat implies more consumption.• While this difference is more significant when comparing flats having

one or two residents, reaching 44%, it becomes very small between flats of two and three residents, around 4%.

• One-tenant flats achieved 30% savings, since it is easier for someone living alone to develop his own energy-efficient practices.

• The margin of potential savings is much bigger in one-bedroom flats.

University of CyprusReasons for Increased Consumption

• Flat 302, 27 years old man, suburban block“I am not willing to sacrifice my comfort to save energy and money. I do not encounter financial problems”.

• Flat 102, male student, urban block“I have my computer equipment working 24/7, and I can not do much about it. Using more energy-efficient infrastructure is out of my budget”.

• Flat 305, 31 years old man, urban block“I want my flat warm the whole day and I earn a good salary to afford that”.

University of CyprusGeneral Statistics

• 72% of tenants stated they were actively involved with the competition and this helped them to acquire a more sustainable lifestyle.

• 94% believed that this competition will influence them to save energy in the future.

• 69% considered that the method of comparing consumption with neighbours is a promising way for saving energy.

• 48% used the website for being updated about the competition.• All residents checked the information placed in their notice boxes.• The Facebook application was used by 15% of people.• 89% wanted to be informed in real-time about their consumption.• From them, 88% were willing to buy a product that would show them

their consumption in real-time. They would invest at most 70 Euro for such a product.

• Some of them were surprised when we explained to them that this is possible at these costs. Some people did not even know that such products exist.

University of CyprusSuggestions from Residents

• Feedback through SMS, sent by the utility once per day.• Daily feedback through email.• More detailed electricity bills.• Smart incentives to people to save energy by the government.• Similar competitions with awards from the utilities.• Scalar pricing schemes that reward green flats and houses while

punishing energy-wasting buildings.• Grants from the utilities or the government for renewable energy

systems and green lighting.• More pervasive and real-time energy feedback techniques.


In most European countries, including Cyprus, people receive an electricity bill once every month. It is not easy for them to perceive their electricity footprint, i.e. to understand whether their consumption is low, medium or high.

Citizens need an effective way to realize the “semantics” of their electrical consumption!


Electrical information is aggregated in neighbourhood level (PO code, street).


• Energy Awareness through Social Comparisons

Social comparisons may enable people to perceive the amounts of their consumed electrical energy, by comparing it with their social and local environment!

Online social networking sites constitute promising platforms to locate people and discover their social networks.

University of CyprusSocial Electricity

Electricity data is real and accurate, provided by the Electricity Authority of Cyprus (EAC).

Social Electricity Facebook application

Electrical information is aggregated in neighbourhood level (PO code, street).

University of CyprusSocial Electricity: Features

• Personal Comparisons: Compare your electricity footprint with the average amount of electricity consumed at your neighbourhood, village/town or the whole of Cyprus.


• Social Comparisons: Compare the electrical consumption at your street with that consumed by the streets of your friends, who are tagged on the map of Cyprus where they live.


• Location-based Statistics: Observe the most and least energy efficient streets in your neighbourhood as well as the most and least energy efficient areas and villages around Cyprus.


• Historical Comparisons: Compare the energy behaviour of your

street in previous months or at the same month in previous years. Make this comparison more social by including the energy behaviour of your friends’ streets.

University of CyprusSocial Electricity: Initial Facts

More than 1,000 users after 4 months, 1,280 likes on our Facebook page.

Eponymous supporters like the Interior Minister Mrs Eleni Mavrou and the Commissioner for the Environment Mr Charalambos Theopemptou.

The most popular group of users (39%) is between 25-34 years old. Younger people between 18-24 are also highly interested (32%).

48% of users live in the capital of Cyprus, Nicosia.

The application started officially at 1st August 2012.

65% of users live in an urban environment.


Extensive reportages and publicity in large media of Cyprus (TV channels, radio channels, newspapers, magazines, online blogs).


First prize award at the 2nd Green ICT Application Challenge, organized by the International Telecommunication Union (ITU).

University of CyprusSocial Electricity: Initial Evaluation

• Via questionnaires. 178 subjects.

44% found the app very useful. 36% found it just useful.

55% were affected positively to become more energy-aware.

16% believed their energy consumption was high. 78% perceived their “energy profile” through the app.

62% claimed their consumption was reduced in regard to last year.

57% are aware of their “green” and “red” friends.

48% used the app from curiosity. 71% for environmental reasons. 71% for financial reasons. 14% for responsibility as a citizen.

Most popular incentive for energy reduction is discount on the bill.

38% believe the app will be more useful in a few years.

64% believe the app will reduce their consumption more than 10%.

University of CyprusSocial Electricity: Current Work

A newsletter sent by email to the users of the application every two months, to inform them about their electricity footprint, comparing it with their local and social environment.(42% opened the email, 13.3% opened the app)

Mobile apps for mobile Facebook users.

University of CyprusSocial Electricity: Current Work

More effective electrical comparisons between people that share common house preferences (e.g. home size, number of residents, heat type).

Access to Social Electricity by people who do not have Facebook through a Web site that offers location-based statistics and general information.



University of CyprusIntegrating Smart Homes to the Smart Grid

• The Smart Grid of Electricity

• A smart grid describes the future electricity grid, enhanced with ICT and smart metering, applied to generation, delivery and consumption of electric power.


• Great potential towards a coordinated, large-scale plan for energy efficiency.

Integrating Smart Homes to the Smart Grid

• The role of smart homes at the future Smart Grid


• Web-based, Grid-ready Smart Homes

Resource URL Method Parameters Return Value

HouseName/electricity GET - JSON

HouseName/reduceconsumption POST reduction (Integer) text/plain

HouseName/increaseconsumption POST maxincrease (Integer) text/plain


• Device Categorization according to usage patterns

• Permanent devices: Should never be turned off.

• On-demand devices: Utilized by home residents spontaneously.

• Schedulable Devices: Devices that are supposed to accomplish some specific task, but their operation is not momentarily urgent and can be postponed for a future time.


• Schedule electricity-related tasks for future execution.

Demand Response

Offering dynamic tariffs, according to supply conditions and current demand..


• A RESTful Web server simulates DR functionality for EAC.• Event-based push notification of tariff changes in real-time.• Integration of a task scheduling mechanism to the framework.• Define the duration of each task, max. amount of waiting time etc.

Demand Response

• Example Scenario: Perform the washing when the tariff falls below 5%.


• Monthly savings can be summed €6.00 in 10% tariff reduction, up to €19.00 in case of 30% reduction (using a tariff 20,07 cent/kWh).

• Possible reduction in the bill of a typical home 3-10%.

Demand Response

• Case Study: Identify schedulable devices and usage patterns

University of CyprusLoad Shedding

An action taken to prevent frequency abnormal operation and is the last resort to maintain frequency stability in case of contingency scenarios or autonomous-islanded operation.conditions.

University of CyprusLoad Shedding: Controller Simulation• Virtual Phasor Measurement Units have been assumed, capable of measuring the frequency and its first derivative online in real-time.

• System parameters were identified by applying the Lyapunov Synthesis Method.

• Based on a simple linear second-order system frequency response (SFR) model.

• Identify the parameters of the plant by employing a suitable Lyapunov function, in terms of state variables and time, forcing this function to be at least negative semi-definite in order to obtain the desirable stability.

• A (low-level) smart grid controller was simulated on Simulink, its main task was to maintain the stability of the system by determining the optimal (per unit) amount of electric load that should be shed to achieve frequency stability.

Parameter Value

Simulator Time Step 0.27424 msec

Total Simulation time 150 sec

Sampling Rate for Domestic Consumption 350 msec

Total Number of HTTP requests 428

University of CyprusLoad Shedding

• Permitted limits +/- 3 Hz.• No load shedding causes under-frequency abnormal operation.• Conventional practices exceed the desired levels for 4 seconds and

need 35 seconds to "absorb" the disturbance.


• Other potential applications:

• Peak Leveling/Shaving• Fault Tolerance• Billing• A Market for Generation/Consumption of Electricity



University of CyprusBeyond the Smart Home

• From smart homes to smart spaces


• Online Social Networking of the Physical World


Evaluation:

• Nine workers at the farm - two weeks duration of experiment.

Impressions:• “The application is easy to be used.”• “Excited with the perspective of controlling the greenhouse while

amusing with my friends.”• “The notifications are quite difficult to understand.”• “The user must be online to be notified!”• “I increased my monitoring activity.”• “I became more aware about the farm.”• “How much does it cost to fully automate the farm?”• “This can be applied also in health monitoring!”

Beyond the Smart Home


• Environmental Awareness in the Urban Environment

• A “meta-smart home” perspective.• Web-based smart homes as the foundational elements

for shaping the next-generation digital cities.• Community-based, real-time sensor sharing.• Location-based discovery of sensors through Cosm. • The UrbanRadar mobile application.


• Global Discovery of Environmental Services





• Exploit the existing Internet infrastructure to achieve real-time discovery of embedded devices and environmental services.



100 500 1000 10000 100000 1M57.00

57.50

58.00

58.50

59.00

59.50

60.00

60.50

61.00

61.50

sensors

mse

c


• A flexible application-level solution for home automation based on combining Web technologies.

Conclusion: General Overview


• Support various interaction types (Ad hoc, pull, push).• Uniform access to heterogeneous home devices.• Multi-hop wireless communication, plug and play functionality.• Reliable operation, masking transmission failures.

• Flexible design, light implementation. • Direct access for residents to their home environment.• Concurrent, multi-resident support.• Interoperable programming interfaces for end user development

of smart home applications.• Graphical user interfaces.

• Small waiting times for simultaneous requests.• Acceptable performance in terms of response times and battery

lifetime of devices.• Scalability.

Conclusion: Meeting Requirements


• Web technologies for interoperability.• IPv6 is a feasible technology for home automation.• Web techniques for advanced performance.• Web-enabled smart homes promote the development of

real-world pervasive applications.• Request queues for improved performance, reliability.• Energy awareness through social incentives.• Smooth integration with the smart grid.• Beyond the smart homes.

Conclusion


• Security• Privacy• Energy conservation• M2M• Semantics• A killer application.• Fairness

Open Issues

Thanks for your attention!

Contact Details: Andreas Kamilaris Email: [email protected]

University of CyprusAcknowledgments