| Intelligent agricultural information system based on Internet of things and computer information technology is an important direction of agricultural development in the future.Data collection is an important part of the intelligent agriculture system,which is mainly realized by various sensor devices deployed in the agricultural production site.However,as the functions of intelligent agriculture systems become more complex,the number of sensors deployed is increasing.The widespread use of large-scale sensor devices leads to higher and higher energy consumption of the system,especially for some devices that cannot be wired for power supply.How to ensure their endurance becomes an important problem to be solved in the future construction of agricultural Internet of things.As a result,based on the wisdom of agricultural greenhouses terminal sensing equipment and energy saving optimization problem as the research object,this paper proposes a multi-objective optimization method based on ant colony algorithm,so as to guarantee the intelligent terminal equipment in the implementation of various data collection and information interaction in the process of low energy consumption,with its solving intelligent agricultural greenhouse intelligent terminal high energy consumption,short battery life problem.The main research contents of this paper are as follows:1)Based on the basic principles and objectives of intelligent terminal energy consumption optimization of agricultural greenhouses,the design ideas and principles of the multi-objective optimization model are analyzed,the structural design of the multi-objective optimization model of intelligent agricultural greenhouses terminal energy consumption is completed,and the detailed theoretical design is given from the design and configuration of the core matrix.2)Based on the multi-objective optimization model of intelligent agriculture greenhouse terminal energy consumption established in this paper,ant colony algorithm is used to design the optimization of its energy consumption.A multi-objective optimization model based on ant colony algorithm(aco)was established by analyzing the wake up time and CPU consumption of intelligent terminal equipment,and the solving method of improved aco was given.3)The experimental system was designed with C language under the environment of VS2017,and the multi-objective problem solving of ant colony algorithm was simulated and analyzed through the experimental system.Finally,the simulation results show that the performance of the algorithm in this paper is improved by 20% compared with the traditional algorithm,and the overall efficiency is improved by 6 times,which can well meet the optimized application of energy consumption of intelligent greenhouse agricultural intelligent terminal. |
