A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Masters of Science in Embedded and Mobile Systems of the Nelson Mandela African Institution of Science and Technology
The applications of Wireless Sensor Networks (WSN) and Internet of Everything (IoE) has
changed how we obtain and consume information. Traditional farming has come a long way in
accepting scientific methods to improve production. Smart Agriculture is one of the ways
technology has greatly contributed to maximized crop production. Centrally placed labs and
mobile soil labs have played a key role in this improved way of farming. Soil samples are
collected from farms and analyzed to provide data to farmers, extension workers, and
policymakers. This process takes time and is costly to implement. In addition, the definition of
trends is difficult as replication of sampling requires more funding. This study proposes to
connect end devices in an IoE system bringing in real-time data and at low-cost and also
providing local data at local stations. The system is built incrementally to have a minimum
viable product (MVP) using a combination of Agile and Waterfall methods of development.
The system presents a pilot remote sensor module in a WSN using a Raspberry Pi minicomputer
as an end node and three sensors collecting information on soil humidity and temperature, air
humidity and temperature and soil pH values in real-time. A cloud-based data analysis and
visualization are used. The system supports the ongoing work by soil labs by collecting
information that is close to real-time. The study brings on board real-time data relaying of farm
parameters that make it easier for small scale farm owners, extension officers, soil labs and
other stakeholders to make instant informed decisions.