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Wireless Sensor Networks (WSNs) play a crucial role in Precision Agriculture by providing real-time data on various environmental parameters like temperature, humidity, soil moisture, etc. However, the efficient utilization of energy in the sensor nodes of WSNs is a major challenge that needs to be addressed. To address this issue, a new multi-objective clustering approach is introduced in this work for grouping the sensor nodes of WSNs. Moreover, a multi-objective hybrid optimisation technique called Election based Aquila Optimizer (EAO) which is the combination of Aquila Optimizer (AO) and the Election-Based Optimisation Algorithm (EBOA) is proposed in this work to make sure that the Cluster Head (CH) selection process in WSNs to identify the best CH. In addition, the proposed method incorporates the newly developed optimization technique with convolutional neural network (CNN) as an Optimized CNN …