Automatic Irrigation And Recommendation System For Green Plants Based On SSM

With the rapid development of Internet and Internet of things technology,water for crops,lawn and garden greening problems of management system is also widespread attention by people gradually,with the continuous increase in pursuit of a better life,the pursuit of people to be resided to the home environment and continue to improve,many people choose in indoor or outdoor balcony gardens to raise some green plant flowers and plants,in order to improve the quality of life.However,the current people's life rhythm is accelerating,and the lack of green plant maintenance of knowledge,certain plant is difficult to know is whether it is to adapt to the local climate,it is often difficult to choose suitable for clean green plant and difficult to timely,watering right amount of green plant science,then,in view of the family environment of green plant automatic watering system also gradually by more and more people study.At present,there are a lot of using soil moisture sensor technology to collect plants and comparing with set in advance good threshold to determine whether need watering automatic watering system,but they often cannot according to the specifications of the green plant size,timing of water quantity and water,to give scientific guidance,in the absence of the family environment is difficult to use the green plant maintenance experience.In view of the above problems,this thesis designed a set of automatic watering and recommendation system for green plants in home environment by comprehensive use of the Internet of things,sensor technology,combined with Java Web and recommendation algorithm.The collection,display and upload of the temperature and humidity data of green plants are realized,and the plants are automatically watered scientifically.When the hardware is abnormal,it will automatically alarm the users and push the possible reasons to the users immediately.According to the user's area and the efficacy of cultivated green plants,suitable plants are recommended.The main work of this thesis is as follows:Firstly,Java Web technology is used to build a software platform based on the browser/server mode of green automatic water injection.The back-end of this platform adopts SSM(Spring+Spring MVC+MyBatis)framework,and the front-end is developed using HTML5 technology,jQuery and Bootstrap framework.Project development is completed by relying on Maven project management tool and Eclipse platform and deployed on Tomcat server.Secondly,it analyzes the current mainstream recommendation algorithm,advantages and disadvantages and its applicable scope,and designs and realizes the personalized green plant recommendation system according to the user's region and the effect of cultivated green plants by combining the content-based recommendation algorithm.Thirdly,sensors and Internet of things technology are integrated to collect and upload environmental data of green plants and execute server instructions.STM32 regularly upload the data collected by each sensor to the background server after processing through the WIFI module.Meanwhile,it receives irrigation instruction and abnormal alarm instruction and controls the execution of the corresponding module to realize remote manual or automatic management of green plant irrigation.Finally,the system's software and hardware functions and the overall test and analysis,the test shows that the system hardware module runs stable,the software platform is easy to operate,to bring users a good personalized recommendation experience.