IoT-Driven Precision Crop Recommendation System Using LSTM & TSC-NET for Sustainable Agriculture

Andhra Pradesh is a well-known agricultural state with a major contribution to the production of rice, cotton, and chilies it is also known as the “Rice Bowl of India”. Unpredictable weather events have been a concern to the state, it is proving to show a negative impact on the state's farming population, nevertheless the state still contributes materially to the country's cultivation production. on thorough research and historical analysis, it is stated that the food diffidence and conservationist problems arise from the established age-old agricultural methods, these methods are being followed without any systematic scientific pursuit. this study pursues to solve the mentioned problem by transitioning agricultural practices with the use of Internet of Things (IoT) technologies. A preferred multi-class classification model leveraging IoT data. the data primarily includes meteorological parameters such as soil NPK values, temperature, humidity, and more. The hypothesized model, a hybrid of Long Short-Term Memory (LSTM) and Time Series - Convolutional Neural Networks (TSC-NET), which recommends suitable crops for the cropland location, it is accomplished by integrating Time-space data. the food grain acreage in Andhra Pradesh is seen dwindling by 4.2 % in 2022–2023, underscoring the susceptibility of farmers to monsoon failures. In addition, macroeconomically speaking, the slowdown in agrarian development disrupts economy's advancement as a whole, advocating for agrarian development. The IoT -driven crop classification model provides the novel approach to enhance crop selection and optimize production potential. therefore, improving the precision and efficacy of crop forecasting while enabling farmers to make well-informed decisions accounting for soil conditions and climate data. It intends to tackle both macro-level economic concerns and micro-level farmer vulnerabilities, this research levels to improve the sustainability and efficiency of agriculture in Andhra Pradesh in an era of shifting climatic patterns and global agricultural competition.