Advanced crop monitoring using unmanned aerial vehicle with Internet of Things and cloud computing

Abstract

This chapter includes detailed explanation on unmanned aerial vehicles (UAVs), Received Signal Strength Indicator (RSSI) scanning and communication protocols that can be used to maximize agricultural yield. Internet of Things (IoT) devices in agricultural applications can offer important plant data like soil moisture, humidity, temperature and other environmental factors that give valuable insights on plant health. The system uses a Raspberry Pi to scan for RSSI signals and map them corresponding to their geographical coordinates. This analysis could be used to deploy IoT devices in optimal locations that offer least network hindrance. Additionally, cloud computing that allows data access from anywhere and anytime and edge computing that minimizes latency by offloading tasks to devices near the source have been discussed. Artificial intelligence (AI) algorithms and big data analytics assist to make right decisions at the right time to ensure optimal yield, minimal wastage and efficient resource management. This blend of UAVs and IoT tools is not only an inexpensive answer but also provides exact observations into plant parameters and streamlining conclusion with AI-driven algorithms, allowing farmers to manage their crops efficiently.