An Artificial Bee Colony algorithm for Efficient Optimized Data Aggregation to Agricultural IoT Devices Application

Abstract

ABSTRACT The current world have structured and gained numerous advantages from state-of-the-art of digital and computerized technologies. Internet of Things (IoT) has recently started playing a key role in day-to-day lives, stretching perceptions, and having the capability to monitor our surrounding environment. The definition for agriculture is given as the practice, science, or art for soil cultivation, crop production utilizing diverse techniques of preparation and technologies, and marketing of farming’s end products. Farmer efficacy and effectively can be enhanced with Wireless Sensor Network (WSN) installation for agricultural practice optimization. Gathering of data from multiple sensors is done during data aggregation. To optimize the data aggregation, metaheuristic methods are applied. The processes of mutation, crossover, and natural selection, are replicated in the evolutionary algorithm known as Genetic Algorithm (GA). Artificial Bee Colony (ABC) algorithm’s primary benefit is that it does not get trapped in the calculation of their local minima, and that it also considers the global and local search. An Artificial Bee Colony (ABC) algorithm has been proposed.