The 4th KKU International Engineering Conference 2012 (KKU-IENC 2012) “Driving together towards ASEAN Economic Community”

Faculty of Engineering, Khon Kaen University, Thailand, May 10-12, 2012

Low-cost Wireless Sensor Network Node for Agriculture and Disaster Monitoring Applications

Kaerkool Koomrum1 Watis Leelapatra1

1Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002

E-mail: jumboman_sang@hotmail.com, watis@kku.ac.th

Abstract—This paper presents the performance testing of a

prototype of low-cost wireless sensor network (WSN) nodes

which are designed for applications that require deployment of

large amount of nodes such as agriculture and disaster warning.

Our design objectives of the prototype are: minimal monetary

cost, lowest power consumption and smallest physical dimension.

We review our design methodology, then report the measured

performance and comparison result of our prototype WSN to the

available commercial wireless sensor node.

Keywords: wireless sensor network node, agriculture and disaster

monitoring applications

I. INTRODUCTION

In 2011, most of the central region of Thailand encountered flood which damaged the country’s economy in several billion USD. One of the factors that caused such damage was that people were unable to protect their own properties due to lacking of up-to-date information about water level. To mitigate this damage, it is necessary that the automatic water level measurement equipment must be installed in potential flooding area. This equipment consists of water level sensors and a radio transmitter which is capable of sending water level information to the receiver. A Group of these equipments forms wireless connection for passing water level information to the receiver, this network is generally called wireless sensor network. The more numbers of installed water level measurement equipment, the more accurate of information can be obtained. The monetary cost is the major difficulty that prevents deployment of the equipment in large numbers.

We have proposed the design of low-cost wireless sensor network node which primarily aims for flood tracking [1]. In this paper, we explain how the design is implemented and then we compare our design to the commercial wireless sensor node in terms of monetary cost, power consumption, physical dimension and transmission range.

This paper is organized as follows: Section II reviews the embedded system design methodology that we used in this work and briefly explains our design process. The experimental result is presented in Section III.

II. SENSOR NODE DESIGN

Sensor nodes can be considered as embedded system which comprise of hardware and software components that are tuned to achieve specific task. Designing embedded systems requires objectives that have to be met and constraints that have to be satisfied. In this work, we follow the embedded systems design methodology to obtain specification of wireless sensor node prototype.

A. The components of sensor node

Sensor nodes are usually made up of four basic components: sensing unit, processing unit, transceiver unit and a power supply unit as shown in Fig. 1. They may also have additional application-dependent components, such as a location finding system, power generator and mobilizer [2].

In practice, hardware components are available as separated devices or integrated into a single device called system on chip (SoC). Some manufacturers offer low-power microcontroller and RF transceiver chip while some manufacturers offer SoCs that integrate microcontroller core with RF transceiver.

Figure 1. Typical components of a sensor node. [2]

B. Embedded System Design

The process of embedded system design begins with functional requirement which states all operating capability of the system [3]. After having requirement, it must be transformed into technical specification and then the designer must decide whether functions must be assigned to hardware

Sensor

Power generator (optional)

Power unit

Processor

Storage ADC Transceiver

Location finding system

(optional)

Mobilizer

(optional)

Sensing unit Processing

unit

K. Koomrum et al. / KKU-IENC 2012, Thailand, May 10-12, 2012

or software components. At this point, components of the system become clearer and system optimization can be conducted. If the requirements are achieved and constraints are satisfied, then the process terminates, otherwise the process repeats. During the optimization, candidate components are substituted in the design and their corresponding parameters are evaluated according to objective functions and constraints. In our work, we focus only on hardware optimization that seeks a solution of system component that has the lowest cost, power consumption and circuit board area occupied by hardware components.

In this work we reduce this process by eliminating hardware/software partitioning process. Only hardware optimization is to be conducted. Our objective is to find a solution of system component that has lowest hardware cost, power consumption and circuit board area occupied by hardware components, hence the objective function in normalized form is:

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and cost � is the function of component cost, power � is the function of power consumption, area � is the function of circuit board area, max_cost � is the maximum cost, max_power � is the maximum power consumption, max_area � is the maximum circuit board area, memory_size � is the size of program memory of

microcontroller.

In our case, we ignore footprint area of glue logic and passive devices.

The constraint we have is the smallest size of program memory that microcontrollers must have in order to accommodate the wireless protocol stacks and the user program.

C. Hardware configuration and solution finding

We have collected interested attributes of hardware components available for implementation from official datasheets provided by their manufacturers. Sample of these

attributes are shown in the Appendix. We wrote a program for finding the solutions according to our objective function to identify the hardware configuration with the lowest hardware cost, power consumption and PCB occupied area.

In our experiment, we create a database of available hardware and their possible hardware combination i.e., a transceiver chips must be operated with a microcontroller and a SoC.

After obtaining all of possible hardware combinations from available component, which is totally 520 different combinations, we evaluate the objective function and obtain the result as shown in Fig. 2. Sample of hardware combinations and their corresponding overall cost are shown in Table I.

Figure 2. Solution of the objective function. [1]

TABLE I. SAMPLE OF POSSIBLE HARDWARE CONFIGURATIONS. [1]

Hardware Object Function Value

CC2430 2.7116

MSP430F148 + CC2420 1.9966

MSP430F5437 + CC2520 2.3625

MC13213 2.6792

MC9S08QE64 + MC13201 2.5395

MC9S08QE128 + MC13201 2.2916

PIC18F44K20 + MRF24J40 0.6289

PIC18F44J10 + MRF24J40MA 1.2903

ATmega644PR231 1.9754

ATMEGA644 + AT86RF230 1.7631

Xbee-Pro 3.0000

Em250 2.7797

From total of 520 combinations, the hardware combination

that yields the lowest overall cost according to the objective function is PIC18F44K20 combined with MRF24J40 transceiver.

After we obtained the desired hardware solution, we use this information to design the wireless sensor node as shown in Fig. 3 which illustrates the schematic of the wireless sensor node. In the schematic, there are 3 semiconductor devices: microcontroller, RF transceiver and voltage regulator. Fig. 4 shows the actual hardware implementation of the schematic in Fig. 3.

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Possible combinations of MCUs and TransceiversPIC18F44K20+MRF24J40

Solution

The 4th KKU International Engineering Conference 2012 (KKU-IENC 2012) “Driving together towards ASEAN Economic Community”

Faculty of Engineering, Khon Kaen University, Thailand, May 10-12, 2012

Figure 3. Schematic of WSN node. [1]

D. Firmware

In software part, we have to choose the wireless communication protocol that allows us to implement the network connection and such protocol must occupy minimal memory footprint (less than 16KB). In our design we chose MiWi which is a proprietary protocol from Microchip because it is flexible and more importantly, it is available to users at no cost.

III. EXPERIMENT AND RESULTS

In this section, we present the performance of our prototype and compare to that is of the commercial XBee Pro wireless module as shown in Fig. 5.

After prototype construction, we take measurement of the prototype for the interested parameters value as shown in Table II. It can be seen that our design is almost 3 times less expensive than the XBee Pro module and consumes 38% less power.

The next experiment, we measure signal transmission pattern of the prototype using wireless signal sniffer CC2430DB as the receiver in open field. The distance from the prototype and the receiver is measured when received signal strength indication (RSSI) reached -92 dBm [4]. We repeated distance measurement in different angles to obtain circular pattern as shown in Fig. 6. The same process is employed to obtain the pattern for XBee Pro as shown in Fig. 7.

Figure 4. Wireless sensor node prototypes.

Figure 5. XBee Pro module.

K. Koomrum et al. / KKU-IENC 2012, Thailand, May 10-12, 2012

TABLE II. MEASUREMENT PERFORMANCE AND COMPARISON OF

PROTOTYPE AND XBEE PRO.

Prototype XBee -Rro

Cost 541.58 Bath 1580.85 Bath *

Power Consumption Run: 168.346 mW Sleep: 27.444 mW

Run: 263.972 mW Sleep: 28.284 mW

Physical Dimension 4266 mm2 1948 mm2

Antenna type PCB Whip * From http://th.element14.com on 3 February 2012

The average transmission range of our prototype is about 122 meters, while the XBee Pro can transmit signal up to 180 meters in average of all directions which is about 32% farther than our transmission range with more evenly area coverage.

The last experiment, we connect the temperature sensor to our prototype and test for actual data transmission. Fig. 8 shows the connection between our prototype and the sensor. The receiver node is attached to PC and received data are shown in Fig. 9.

Figure 6. Transmission range of the prototype measured at RSSI = -92 dBm. (in meters)

Figure 7. Transmission range of the XBee Pro module measured at RSSI = -92 dBm. (in meters)

Figure 8. Connection between temperature sensor and the prototype

Figure 9. Received data (temperature and humidity) is displayed on PC

IV. CONCLUSIONS AND FUTURE WORK

We have proposed the design and implementation of low-cost wireless sensor node which is suitable for applications that require large amount of sensor nodes to be deployed. Although the prototype cannot overcome the commercial wireless module in some aspects such as transmission range and physical size, but it achieves our primary goal which is the minimized monetary cost. The next phase of our work will be about construction of wireless sensor network consisting of our prototype nodes which will be tested for overall networking performance.

ACKNOWLEDGMENT

The work is supported by Telecommunications Research and Industrial Development Institute (TRIDI), Thailand.

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The 4th KKU International Engineering Conference 2012 (KKU-IENC 2012) “Driving together towards ASEAN Economic Community”

Faculty of Engineering, Khon Kaen University, Thailand, May 10-12, 2012

REFERENCES

[1] K. Koomrum and W. Leelapatra, “Design of Low-cost Wireless Sensor Network Node for Flood Tracking in Thailand,” Proceeding of the 34th Electrical Engineering Conference, 2011, 34, pp. 1081-1084.

[2] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks (Elsevier), 2002, 38(4): 393-422.

[3] P. Marwedel, “Embedded System Design,” Netherland, Springer, 2006.

[4] Texas Instrument, “CC2430 A True System-on-Chip solution for 2.4 GHz IEEE 802.15.4 / ZigBee” , 2009.

Appendix

TABLE III. HARDWARE AVAILABLE FROM TI. [1]

Hardware Type Device Price/Unit 1

CC2420 Transceiver CC2420 8.75 $

CC2430 SoC CC2430F32 10.00 $

CC2430F64 11.11 $

CC2430F128 12.54 $

CC2431 SoC CC2431 14.84 $

CC2520 Transceiver CC2520 6.45 $

CC2530 SoC CC253032 9.01 $

CC253064 9.41 $

CC2530128 9.81 $

CC2530256 10.2 $

1. From www.digikey.com on 10 Jun 2010

TABLE IV. HARDWARE AVAILABLE FROM MICROCHIP. [1]

Hardware Type Price/Unit 2

MRF24J40 Transceiver 4.3 $

MRF24J40MA Transceiver Module 9.95 $

MRF24J40MB Transceiver Module 26.58 $

PIC18F24J10 MCU 2.12 $

PIC18F44K20 MCU 2.7 $

PIC18F44K22 MCU 3.06 $

2. From www.digikey.com on 10 Jul 2010

TABLE V. HARDWARE AVAILABLE FROM FREESCLAE. [1]

Hardware Type Price/Unit 3

MC13201 Transceiver 3.71 $

MC13202 Transceiver 4.36 $

MC13211 SoC 4.95 $

MC13212 SoC 6.26 $

MC1321 3 SoC 6.84 $

MC13224V SoC 8.75 $

3. From www.digikey.com on 26 Sep 2010

TABLE VI. HARDWARE AVAILABLE FROM EMBER. [1]

Hardware Type Price/Unit4

Em250 SoC 6.16 $

Em351 SoC 7.6 $

Em357 SoC 7.9 $ 4. From www.digikey.com on 30 Nov 2010

TABLE VII. HARDWARE OF JENNIC. [1]

Hardware Type Price/Unit5

JN5139 SoC 14.04 $

JN5148 SoC 14.7 $ 5. From www.digikey.com on 30 Nov 2010

TABLE VIII. HARDWARE OF MAXSTREAM. [1]

Hardware Type Price/Unit6

XBee SoC 19 $

Xbee-Pro SoC 32 $ 6. From www.digikey.com on 30 Nov 2010

TABLE IX. HARDWARE OF ATMEL. [1]

Hardware Type Price/Unit7

AT86RF230 Transceiver 3.7 $

AT86RF231 Transceiver 4.73 $

ATmega644PR231 SoC 10.45 $

ATmega64RZAV SoC 5.88 $

ATmega1281R231 SoC 15.48 $

ATmega128RZAP SoC 9.05 $

ATmega256RZAV SoC 10.74 $

7. From www.digikey.com on 30 Nov 2010