Browsing UAF Graduate School by Subject "precision farming"
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A two-layer energy-efficient wireless sensor network for precision agriculture applicationsThe agriculture industry has benefited from the recent technological evolution; for example, farmers now use satellite images to monitor large fields. The use of technology in agriculture, generally referred to as Precision Agriculture, has attracted a lot of research interest from electrical engineers. One particular area of Precision Agriculture is the application of embedded systems in monitoring large crop fields. Sensor nodes are placed at various locations in the field where they measure different parameters, such as temperature and soil moisture. The collected measurements are sent to a central hub outside of the field where they can be further processed and displayed for the farmers to make appropriate decisions. From the farmers' perspective, this kind of wireless sensor network (WSN) is a cost-effective solution that allows them to gather accurate information about their crops in real time and significantly improve production. To scientists, it provides invaluable information that can help them improve farming processes or even develop new crop varieties. From the embedded systems stand-point however, such a network poses several challenges, mainly battery life and network lifetime. Battery life is a serious challenge because nodes are scattered in the field and it would be labor intensive and expensive to replace their batteries. It is important to keep nodes alive because dead nodes not only fail to collect data but they also fail to relay packets from other active nodes. Radio communication draws most of the node's battery in WSN, so most energy saving techniques revolve around careful management of the radio. In this study, we focus on routing protocols that maximize the lifetime of the network. Most researchers have suggested various routing schemes to minimize battery consumption by finding the shortest path to a hub; however, when looking at the network as a whole, this approach may not be ideal. We present a lifetime-maximizing routing scheme that uses a cost function to distribute the traffic load among all nodes and to spare those with low remaining energy. The cost function being essential to our algorithm, we evaluate the impact of different types of cost function on the network lifetime. Lastly, we evaluate the impact of link quality in the cost function. Simulation results show that the power cost function has the best performance and that link quality can improve network lifetime. Another major contribution of this research is the design of a test framework that can be used to evaluate other routing protocols. In order to evaluate our routing protocol, we created a WSN simulation in Castalia. The simulation and the routing protocol are highly parametric and with minor modifications, users can experiment with new protocols or variations of ours. Using our platform can save users a lot of time and trouble, especially those unfamiliar with simulation tools, hence allowing them to focus their efforts on their protocol.