Characterization of wireless mesh network performance in agricultural environments

Summary form only given. Wireless sensor and actuator networks will play an increasingly important role in farms and orchards as orchardists and farmers seek more effective ways to implement processes for pest control, precision irrigation, fertilizer delivery, frost detection, fire detection, detection of crop maturation, silage monitoring and livestock tracking. However, wireless propagation in agricultural environments is severely affected by the excess path loss due to the presence of vegetation along the signal path. Practical experience has shown that wireless mesh networks deployed in such environments often behave significantly different than expected. Until recently, designers have relied almost exclusively on relatively small amounts of wireless propagation data collected manually at great expense. As wireless sensor and agricultural networks mature and are being deployed in greater numbers as part of extensive field trials, more operational field data has become available from a larger number of sites and for longer of periods of time. The recent deployment of hundreds of such networks across Canada, Europe and the United States by a startup company and their willingness to provide us with access to both performance and weather data logged over one or more complete growing seasons has provided us with an unprecedented opportunity to apply data mining techniques and answer many important questions concerning the manner in which wireless propagation affects the performance of wireless mesh networks in such environments. The results obtained through such data mining nicely complement results obtained through manual measurements or simulation. Our findings fall into three categories: 1) the manner in which meteorological factors affect wireless mesh network performance, 2) the manner in which spatial factors affect network performance, and 3) the degree of randomness in network performance which cannot be directly attributed to easily discerned physical caus- s. The results have important implications for the design of future wireless networks in agricultural environments.