An Internet of Things Platform for Improved Water Management Using Underground Soil Moisture Sensing

Efficient use of water resources is becoming of paramount importance in agriculture due to their scarcity and less predictable availability impacted by climate change. Profitability of traditional farming methods to meet the increasing population demand for food production has been negatively affected, thus requiring efficient irrigation systems and water management practices through technology. In this thesis, a cost-effective Internet of Things - IoT platform that incorporates underground soil moisture sensing is presented with the aim of increasing the penetration of applied technologies in the farming market. The platform features a Sub-1 GHz IEEE802.15.4g-based wireless sensor network concentrator (WSNC) with LTE backhaul which provides Internet connectivity in rural areas towards a cloud server. The WSNC connects sensor nodes to the collector node over a wireless link following a star topology network. The sensor node is enhanced with a helical antenna designed specifically for underground operation along with a power amplifier to compensate signal attenuation in the soil-air path to the WSNC. Based on the number of collectors and physical layers that are supported, the implemented WSNC offers three configurations: Single Collector (SC), Multi Collector (MC) and MC - Multi Rate (MR). The SC-WSNC supports a total of 50 sensor nodes whereas the MC-WSNC can support up to 200 devices by hosting several independent Wireless Sensor Networks (WSNs) operating on a unique frequency channel. To improve the system performance, a load balancing algorithm and a sensor handover mechanism are developed for the MC-WSNC to uniformly distribute the number of aggregated sensor nodes across the available collectors. The MR capability added to the MC-WSNC and the sensor nodes dynamically optimizes the energy consumption and radio link margin of the sensor nodes for improved battery lifetime and connection reliability. The SC-WSNC has been experimentally evaluated in terms of coverage range in aboveground and underground scenarios with a detailed end-to-end delay characterization using state-of-art tools in every network segment. The results reveal the limitations of the system in covering large farming areas due to both the high attenuation in the combined physical media and the limited number of sensor nodes that can be attached to one collector. In contrast, the MC-WSNC is evaluated using a test-bed consisting of up to four co-located collectors and fifty sensor nodes. The performance evaluation is carried out under race conditions in the WSNs to emulate high dense networks with different network sizes and channel gaps. The experimental results show that the MC-WSNC proportionally scales up the capacity of the network and reduces both the energy consumption and the packet error rate of the sensor nodes. The MR feature - implemented as a physical layer switch at the sensor nodes - further reduces the overall network power consumption and increases the network throughput while at the same time accounts for varying radio link conditions.