Real Time Assistance to Farmers and Health Sector

Abstract

Nowadays, it is very difficult to carry plants and crops and take it to the agriculture specialist. Due to time delay the condition of plants get worse which causes wealth issues to farmer. Bringing agriculture specialist to the plants and crops is expensive. In rural areas, it is difficult to travel from one place to another to consult the specialist as there is limited number of agriculture specialists. Our system is to provide the real time assistance to farmers by using mobile application and hardware system which tracks plants environmental data by sensors and then cross-references this information through Wi-Fi with plant databases on server. Health care service will be provided to examine the disease and give medical recommendations as described in [1]. The tools/technologies are Android Studio, Local Host, PyCharm, Java, Json, XML, Python and keras.sequential model with 2D convolution layer known as conv2d with Machine learning. Temperature, humidity and moisture sensors are used in this project and we adopted the Incremental model for implementation. The project aim is to timely treat the crops and facilitating the farmers by providing them reliable and cost effective information as presented in 2