Transformer-Based IoT Environment Monitoring And Prediction System

With the continuous development of technologies such as artificial intelligence,big data,and cloud computing,the application scope of the Internet of Things(Io T)and embedded systems is constantly expanding,bringing new opportunities and challenges to the development of agriculture.In traditional agriculture,environmental and crop monitoring mainly relies on manual sampling and equipment such as meteorological stations,and the monitoring scope and accuracy are relatively limited.With the introduction of Io T and embedded systems,agricultural monitoring has become more intelligent and accurate,while also saving a lot of manpower and material resources.Precision agriculture refers to the precise and efficient agricultural production management mode achieved through modern technology,combining the dynamic characteristics of natural,economic,and social environment of agricultural production.The key to achieving precision agriculture is the precise monitoring and fine control of the agricultural environment.Currently,meteorological prediction methods mainly rely on data from meteorological stations,but they often cannot adapt to local situations such as isolated greenhouse plantations or special mountainous areas,therefore,Io T and embedded systems are needed to achieve precise monitoring and control of the agricultural environment.In most scenarios of agricultural production,environmental information has the characteristics of time series information such as large time span and strong periodicity.At present,the mainstream method to solve the problem of time series information prediction is to use recurrent neural network,but this method often has problems such as time-consuming calculation and gradient explosion.Recent studies have shown that the Transformer structure based on the attention mechanism has shown great performance advantages and feasibility in solving the prediction problem of temporal information.Therefore,this paper designs an Io T environment prediction and monitoring system.The system uses embedded systems and Io T technology to design a set of embedded hardware acquisition platform,and collects the surrounding environment information(temperature,humidity,light intensity,CO2 concentration),and report these data to the cloud server in real time.At the same time,the host computer software is also designed,which can make the environmental data collected by the cloud server into a data set,and use Transformer for training and prediction.In addition,the embedded system also designs a set of control algorithms that can combine monitoring data and forecast data to control the water supply and ventilation modules to achieve precise control of the surrounding environment.In short,the research of this paper aims to bring new ideas and technical support to agricultural production management,realize the refined and efficient management of agricultural production,and make positive contributions to ensuring food safety and sustainable agricultural development.