An IoT Crop Recommendation System with k-NN and LoRa for Precision Farming

Choosing the planting site is a complex and decisive task for crop success, but data can help with this task. Wireless Sensor Networks can capture large volumes of data, but manual analysis may be impossible depending on the number of devices and sensors deployed. Furthermore, Machine Learning techniques are handy for processing data and detecting patterns and are widely used nowadays. The union of these two technologies is promising, presenting itself as a path to precision agriculture. This paper proposes a system based on Wireless Sensor Networks capable of detecting the best regions for planting. The system uses LoRa technology for excellent coverage and local processing, eliminating the need for the Internet.