Architecture and Performance Evaluation of IoT- Enabled Wireless Sensor Networks in Precision Crop Monitoring

The combination of Internet of Things (IoT) and Wireless Sensor Networks (WSNs) has transformed the practice of the modern agricultural sector by providing the possibility to monitor the crops precisely, make decisions immediately, and take care of the resources. Conventional agricultural practices tend to assume homogenous application of inputs and manual monitoring, which ignore spatial and temporal changes in the soil, climatic and crop conditions which result in wasteful utilization of water, fertilizers and energy. IoT based WSNs overcome this shortfall by supporting distributed sensor nodes that continuously gather environmental and crop related data such as soil moisture, temperature, humidity, nutrient level, and health of the plant. They have low-power microcontrollers (e.g., ESP32, Arduino, NodeMCU) and can be connected through wireless networks, including LoRaWAN, Zigbee, WiFi, and NB-IoT, sending data to wireless access points (gateways), and cloud or edge computing platforms to be processed and analyzed. Predictive insights, early alerts to crop stress, pest infestations, and nutrient deficiencies can be made through advanced machine learning models and edge AI with 92-95.9 percent success in environmental and crop condition prediction. According to performance reviews, there are vast energy efficiency improvements (up to 67 percent), resource use (water and fertilizer savings up to 40 percent), network reliability (PDR >95 percent), and crop yield (up to 30 percent). The selection of the protocol, hierarchical clustering (LEACH), and the low-power architecture make network lifetime and coverage to be optimized. The main issues are environmental interference, power constraint, security of data as well as interoperability between heterogeneous sensors and communication protocols.