paper no: 200000 - college of engineering - purdue …mohtar/iet2007/073077.doc · web viewradio...

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Author(s)

First Name Middle Name Surname Role Email

Martin A Hebel ASABE Member

[email protected]

Affiliation

Organization Address Country

Southern Illinois University Carbondale

1365 Douglas DriveASA Room 106Carbondale, IL 62901-6614

USA

Author(s) – repeat Author and Affiliation boxes as needed--


Ralph F Tate [email protected]

Affiliation



1365 Douglas DriveASA Room 106Carbondale, IL 62901-6614

USA

The authors are solely responsible for the content of this technical presentation. The technical presentation does not necessarily reflect the official position of the American Society of Agricultural and Biological Engineers (ASABE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Technical presentations are not subject to the formal peer review process by ASABE editorial committees; therefore, they are not to be presented as refereed publications. Citation of this work should state that it is from an ASABE meeting paper. EXAMPLE: Author's Last Name, Initials. 2007. Title of Presentation. ASABE Paper No. 07xxxx. St. Joseph, Mich.: ASABE. For information about securing permission to reprint or reproduce a technical presentation, please contact ASABE at [email protected] or 269-429-0300 (2950 Niles Road, St. Joseph, MI 49085-9659 USA).

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Author


Dennis G Watson ASABE Member

[email protected]

Affiliation



1205 Lincoln Dr, AG 176Carbondale, IL 62901-6614

USA

Publication Information

Pub ID Pub Date

073077 2007 ASABE Annual Meeting Paper


An ASABE Meeting Presentation

Paper Number: 073077

Results of Wireless Sensor Network Transceiver Testing for Agricultural Applications

Martin A. Hebel, Asst. ProfessorElectronic Systems Technologies, Southern Illinois University Carbondale, [email protected]

Ralph Tate, Asst. ProfessorElectronic Systems Technologies, Southern Illinois University Carbondale, [email protected]

Dennis G. Watson, Assoc. ProfessorPlant, Soil and Agricultural Systems, Southern Illinois University Carbondale, [email protected]

Written for presentation at the2007 ASABE Annual International Meeting

Sponsored by ASABEMinneapolis Convention Center

Minneapolis, Minnesota17 - 20 June 2007

Abstract. Radio frequency propagation for wireless sensor networks in agricultural environments faces challenges due to placement of nodes for wide-area mesh coverage and reliable link quality above crop canopies. Environmental conditions may also have a role in receiver signal strengths. IEEE 802.15.4/ZigBee XBee Pro 2.4GHz wireless sensor network devices were tested to determine distance and height limitations on signal strength. Testing of signal strength and link quality was performed to simulate effects of changing crop canopy heights. Data indicated attenuation and signal strength variance were dependent on line of sight (LOS) losses and heights less than the Fresnel zone radius. Testing of receiver signal strength during heavy precipitation indicated non-uniform losses and variance in signal strength across available frequency channels.

Keywords. Wireless, Sensor, Network, RF, ZigBee


IntroductionWireless sensor networks (WSNs) hold great promise for data acquisition and control (DAAC) in wide-area agricultural use as discussed by Hebel (2006) in his paper on IEEE 802.15.4/ZigBee network issues. The ability to route data between low-cost, battery-powered (or solar-powered) sensors allows large areas of land to be monitored and remote equipment to be controlled cost-effectively.

The ability to communicate between nodes faces challenges where transceivers need to communicate over a crop canopy with little clearance. Signal propagation across the top of crops can lead to reflection, scattering and absorption of radio signals, resulting in greater attenuation and variance in RF signal strength and link quality at the receiver. Humidity and rain may also play a role in the ability to communicate due to scattering, reflection and absorption of the RF signal.

In the transmission of radio frequencies between two nodes, height above the ground and foliage becomes important in that line of sight (LOS) alone is not sufficient. The Fresnel zone, as illustrated in Figure 1, is a volume surrounding the direct signal path that defines a reflection-free zone, thus setting physical bounds for the LOS path. Obstacles (crop canopy, bare ground, etc.) inside the Fresnel zone will result in a higher rate of signal attenuation along the path and fluctuations in received signal strength due to multi-path interference.

Figure 1: Fresnel Zone to Prevent Ground Reflections between Transceivers.

The Fresnel zone radius (FZR) is given by equation (1), where d is the distance between antennas in km and f is the frequency in Hz. For example, a 2.4GHz RF link with a path length of 100m, results in a FZR of 1.77m. In the case where transceivers are operating across a reasonably flat area with low-lying vegetation (as in this investigation), it is generally accepted that antenna heights less than 60% of the FZR will result in dramatic signal attenuation and fading.

(1)

The attenuation of 2.4GHz signals due to rain is calculated as 0.02dB/km for a rain rate of 150mm/hr (Zhao, Zhang, & Wu, 2000). According to “Wireless Antennae LAN FAQ’s”, the loss due to torrential rain should only be 0.05dB/Km for 2.4GHz signals. Testing by Goense and Thelen (2005) showed an improvement in receiver signal strength indication (RSSI) during and shortly after rainfall, though their testing did not identify the reason for the improvement. The low loss and gains in testing seems counter-intuitive since microwave ovens operating at 2.45GHz cause heating through the interaction of the RF energy with moisture in the food.

Testing was performed to determine height-distance losses and the effects of precipitation on 2.4GHz signals as it relates to agricultural environments.

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Data Collection and Analysis

XBee Pro Transceivers

In order to perform quantitative analysis of data to determine placement and use limitation of 2.4GHz IEEE 802.15.4/ZigBee networks in an agricultural environment, XBee Pro transceivers were tested for signal strength and packet transmission under varying conditions for distance-height and precipitation losses. The XBee Pro’s, as shown in Figure 2, operate in the 2.4GHz ISM band using the IEEE 802.15.4 protocol and have the ability to perform routing functions of ZigBee networks. Other features of note for this testing includes: 18dBm (63mW) output power with line of sight transmission distances of up to 1Km.

Unique node addressing scheme.

Clear channel assessment (CCA) to check ambient signal strength prior to transmitting.

Ability to perform point-to-point or broadcast addressing.

Retries for non-acknowledged packet transmissions when using point-to-point addressing.

No retries when using broadcast addressing.

11 channel selections in the 2.4GHz band (channels 12-23: 2410MHz to 2480MHz) to provide frequency separation between personal area networks (PANs) in the same local area.

50mA idle/receive current draw and 200mA transmit current draw.

Sleep mode current draw of 10uA.

Ability to retrieve RSSI level for last reception.

Receiver sensitivity of –100dBm.

Ability to change device configuration using serial data from personal computers or microcontrollers.

Figure 2: XBee Pro IEEE 802.15.4/ZigBee Transceiver

Distance-Height Effects on RSSI Level and Packet Losses

Placing sensor and transceivers at distances of 100m would allow a density of approximately 1 node per acre, though terrain may dictate varying distances to achieve line of sight between nodes. The height of the antennae should not extend excessively above the crop canopy for structural integrity. Testing was performed to determine RSSI levels and packet losses over a range of heights and distances.

Testing was performed on a fairly level groomed grass plain. This provided uniform foliage height and limited variance due to variables such as wind having an effect on foliage and

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resulting signal propagation. Heights of 2m, 1.5m, 1m, 0.75m, 0.5m and 0.25m were tested at distances of 50m, 75m, 100m, 125m, 150m, 175m and 200m to provide analysis of the effect of height and distance. During testing, the heights of transmissions were randomized, and battery replacement was performed halfway through each run to limit possible effects of battery power loss. Both the local data collection base unit and the remote unit were set to the same height to provide data paths that would be typical of routing data between units across the top of the crop canopies for collection at a central local as illustrated in Figure 3. Data would be collected by both Reduced Function Device (RFD) Endpoints, such as A and B, and Full Function Device (FFD) routers. Data would be routed across the crop canopy between nodes to a central FFD Coordinator.

Figure 3: Cluster Networking Example for Communications.

For testing, the base unit used a laptop interfaced using USB to an XBee pro transceiver. The base unit sent a unique data packet to the remote unit with a loop back device installed to transmit back the received data. The base unit would match the transmitted packet to the received unit and record the results of a good or bad reception. 100 packets were transmitted for each height-distance point. Every 10 samples the laptop would request the RSSI level of the received packet and record the data to provide 10 points of dB level per sample point. To ensure any missed data was logged, the base unit was configured to use broadcasting addressing. This prevented the unit from automatically performing retries should it not receive an acknowledgement. The remote unit was configured for point-to-point addressing to help ensure that any packets it successfully received had a higher probability of reaching the base unit. The laptop software performed up to 3 retries, recording each, before logging the packet as missed.

Specialized software was written in Visual Basic for the laptop to perform the transmission of packets, RSSI requests, and transmission retries. Each data sample result was logged to a text file for analysis. Three complete runs were performed 1 week apart in October 2006.

Figure 4 is a plot the result of the mean of 10 RSSI levels (N=10) for each sample point and averaged over 3 runs. Figure 5 represents the same data as bar chart for comparison to later figures.

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Figure 4: Average of 3 Runs of Mean RSSI Level Over Grass Plain

Figure 5: Average of 3 Runs of Mean RSSI Levels in Bar Chart Format(with axis value reversals from Figure 4)

The data indicates the expected trend of decreasing signal strength due to free space losses based on distance and additional Fresnel losses due to height. Anomalies in the data, such as lower signal strengths at 50m distance at the 2m and 1.5m heights are not explained through any variables under test, but individual run data shows similar trends.

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Figure 6 is a graph of the standard deviation of the average signal strength. For the 10 signal strength levels recorded (N=10) per sample point, the standard deviation was calculated and the three runs averaged.

Figure 6: Average of Standard Deviation for RSSI levels over 3 Runs

As the height of the samples lowered beyond the Fresnel Zone radius, notably 100m at approximately the 1.5m height, the reflection of the signal can lead to increased variance in the received signal strength due to multi-path propagation. In Figure 5, the increase in signal variance is visible at distances greater than 100m and heights less than 1m. With a loss of 3dB representing a halving of signal strength, fluctuation of these magnitudes can cause uncertainty in the proper transmission of packets. The variance at the 2m heights, close to the base area, again is not accounted for by tested variables.

The number of retires performed by the base unit is represented in Figure 7. The retries for each sample point were averaged over 3 runs. The base unit performed up to 3 retries before a packet was logged as missed. Data indicates all retries for a given sample point. Relationships between missed data, signal strength and signal variance can be seen though further analysis is required to determine correlations.

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Figure 7: Average Packet Retries of 3 Runs

Using the 18dBm output of the XBee Pro units, the signal strength was sufficiently high at all points to limit missed data packets. Of the over 12,000 packets transmitted during the 3 runs, only 4 packets were recorded missed (0.033%). Only 1 packet was recorded as bad. Due to the nature of the 802.15.4 protocol, error checking should prevent any bad data from being utilized by the receiving unit.

Effects of Relative Humidity and Precipitation on RSSI Levels for a Single Channel

To test the effects of relative humidity and precipitation on RSSI level, a weeklong test was conducted. Remote units were constructed consisting of an XBee Pro module, a BASIC Stamp microcontroller, and a SHT11 humidity and temperature sensor in a ventilated enclosure. The remote unit was placed in a field of winter wheat at a height of 1.5m located 100m from the base unit outside a house. The base unit was connected to a laptop inside the house running StampPlot Pro software to record data. The default channel for the XBee Pro units of 12 (2.410GHz) was used in testing.

The BASIC Stamp read the SHT11 sensor for temperature and humidity, temperature correct the humidity data, and transmitted the data along with a sequence number to the base unit using point-to-point addressing every 5 minutes. Software would record the received data and poll the XBee transceiver for the RSSI level to be logged with the data. Between samples, the BASIC Stamp and XBee would enter sleep modes to conserve power, waking 5 minutes later for another sample.

The test was performed in early January 2006 over the span of 1 week. During this week there was nearly continuous light to medium rain with Relative humidity values ranging between 36%

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and 95%. Over the entire sample period, the mean dBm was calculated to be –62.9 dBm (N=2029) with a standard deviation of 1.18. Changes in signal strength or variance were not identifiable during periods of precipitation.

Of the 2029 samples used for analysis, not a single packet was lost as evidenced by the contiguous sequence numbering of the packets.

The remote unit was powered from 4200mAH Lithium batteries and lasted 7 days and 6 hours. The unit was not designed to be power efficient though power savings were realized using sleep modes between the samples lowering idle power consumption from 55mA to 8mA. The units were configured at their highest setting of 18dBm drawing approximately 200mA during data transmission bursts.

Effects of Precipitation on RSSI Levels Across All Channels

Considering that microwaves operate in the 2.4GHz band for heating, a test was performed to measure RSSI levels during a heavy rain. A remote unit was reconfigured to send data to the base unit and to request channel information from the laptop connected to the base. A randomized sequence of channels on which the XBee Pro operates (12-23) was used. To keep the units synchronized over channel changes, the base operator and software in the remote unit performed the following operation: 15 samples, approximately 2 seconds apart, were collect on the current channel. The RSSI

level at the base unit was recorded upon data reception for each sample.

The base operator would select the next random channel using a drop-down box on the StampPlot software.

The remote unit, after sending a data packet, would poll the base unit's software for the select channel.

If the remote unit detected a change in channel number, it would send a packet to cause the software to change the base unit's channel to the selected channel.

The remote unit would then change to the received channel and send the next data packet.

The remote unit was placed 200m from the base with heights of 2m for both.

Three runs were performed with randomized channel sequences. 15 samples were collected (N=15) for each channel per run. Testing was performed as a violent storm cell entered the testing area producing hail, torrential rain, and moderate rain over the 30 minutes the testing was performed.

Figure 8 is the result of the testing showing the mean of all samples for a channel with bars denoting standard deviation. Above channel 18 a dramatic loss of signal strength and increased variance can clearly be seen.

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Figure 8: RSSI level and Standard Deviation Across Frequency Channels in Rain

Table 1 provides the center frequency of the various channels (Gutiérrez, et al, 2004). With microwave ovens operating at 2.45GHz, it is interesting to note this is the center frequency for channel 20.

Table 1: IEEE 802.15.4 Channel Center Frequencies For Channels 12-23Channel Center Freq.

(GHz)Channel Center Freq.

(GHz)Channel Center Freq.

(GHz)12 2.410 16 2.430 20 2.45013 2.415 17 2.435 21 2.45514 2.420 18 2.440 22 2.46015 2.425 19 2.445 23 2.465

Figure 9 is a similar test performed in dry conditions with relative humidity of approximately 26%. Losses and variance are more equal across the channels.

Figure 9: RSSI Level and Standard Deviation Across Frequency Channels for Dry Conditions

When several PANs are operating the same local area, the results of this test indicate that channels for PAN separation should be kept to the lower ones to prevent excessive losses in outdoor environments.

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Conclusions and RecommendationsThe data collected in these tests show expected signal attenuation due to free-space path loss along the distance between transceivers and show the impact of Fresnel Zone loss as the antenna height was adjusted to emulate the changing height of a crop canopy. These losses would represent the worst-case scenario as it is expected that a crop canopy would not have the density and electrical properties of grass covered ground. This is to be experimentally determined in future work. The large variance in mean values of RSSI measured at antenna heights well below the Fresnel Zone radius is a good indication of multi-path interference. However, even at the extremes of long range and low antenna height, the RSSI was better than 15dB above the published Receiver sensitivity of -100dBm. This is a respectable amount of fade margin and the low number of dropped data packets demonstrated a robust data link in spite of the large attenuation and variance of RSSI values. The frequency dependent signal loss due to rain cannot be explained with simple attenuation models. It is suspected that the rain is causing an increase or change in ground conductivity, affecting the multi-path propagation process. It is also speculated that the increase in water vapor could cause refraction (bending) along the LOS path, thus reducing signal measured at the receiver. Further work will investigate these anomalies in link performance.

ReferencesGoense, D., & Thelen, J. 2005. Wireless sensor networks for precise phytophthora decision

support. 2005 ASAE Annual International Meeting. Paper number: 053099

Gutiérrez, J. A., Callaway, E. H., & Barrett, R. L. 2004. Low-rate wireless personal area networks. IEEE Press, New York.

Hebel, M. 2006. Meeting Wide-Area Agricultural Data Acquisition and Control Challenges through ZigBee Wireless Network Technology. Proceedings of the 4th World Congress, 234 – 239, Orlando, FL.: ASABE.

StampPlot Pro. 2006. V3.7. Carbondale, IL. SelmaWare Solutions.

TeraBeam. 2006. Calculations. Retrieved 12 Dec 2006 from http://www.terabeam.com/support/calculations/index.php

Wireless LAN antennas FAQ'S (n.d.). Retrieved February 14, 2006, from http://wlanantennas.com/wlan_faq_radioprop.htm.

Maxstream. 2006. XBee/XBee Pro OEM RF Modules Product Manual. London, UT: MaxStream, Inc.

Zhao, Z., Zhang, M., & Wu, Z. 2000. An Analytic Model of Specific Attenuation Due to Rain. Digest of The 25th International Conference on Infrared and Millimeter Waves, 471-472, Beijing, China.: IEEE.

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