• DR.R.HEMALATHA
• S MEENA

The Agricultural area is facing numerous challenges together with water shortage, climate exchange, and low productivity due to outdated farming practices. Consequently, there's a dire want to introduce the current era within the agriculture sector to beautify its productivity and performance. This mission affords an IOT based smart Agriculture monitoring device aimed at increasing agricultural productivity by automating and optimizing crop management. The device makes use of diverse sensors to screen environmental situations in real-time. The statistics gathered are processed through a microcontroller and transmitted wirelessly to an internet application that offers farmers with visualized information about their crops. The gadget is designed to be less expensive and easy to apply, allowing farmers to reveal their crops remotely and take vital moves to optimize their increase. By presenting farmers with actual-time facts on their vegetation, the machine can assist them make informed choices regarding water and fertilizer utilization, pest control, and harvesting times. This, in turn, can lead to extended crop yields, decreased costs, and progressed profitability. The project additionally has destiny implications, including the mixing of device learning and artificial intelligence technology to further optimize crop control. The soil fertility is dependent on those factors and therefore it's miles hard to expect. But, the Agriculture sector in India is going through the intense hassle of including crop productivity. Farmers lack the essential expertise of nutrient content material of the soil, selection of crop best acceptable for the soil and additionally they lack green strategies for predicting crop well earlier in order that suitable strategies had been used to improve crop productivity. To estimate soil fertility based totally on macro- and micronutrients found inside the dataset, take a look at provides diverse supervised gadget learning algorithms, including choice timber, K-Nearest Neighbor (KNN), and aid Vector system (SVM) classifiers. The dataset is used to use supervised system studying algorithms, and the take a look at dataset is used to evaluate them.As it depends on numerous variables, soil fertility is hard to forecast. However, increasing crop yield is a critical difficulty for India's agriculture industry. Farmers lack basic expertise about the vitamins within the soil, a way to select crops which are pleasant for the soil, and powerful methods to forecast plants nicely in advance in order that the proper strategies can be applied to boom agricultural yield. The utilization of IoT sensors in cultivating tools can make agriculture processes more effective. Furthermore, IoT innovation can be utilized in cycles like transportation and potential of agriculture objects. Despite the fact that, the usage of IoT innovation isn't always confined to collecting and inspecting information.

Smart Farming, Crop Yield, Precision Agriculture , Data Mining, Internet of Things.

"ENACTING SMART STRATEGIES & IMPROVING CROP PRODUCTION USING DATA MINING TECHNIQUES IN PRECISION AGRICULTURE ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.d642-d650, November-2023, Available :http://www.jetir.org/papers/JETIR2311379.pdf

"ENACTING SMART STRATEGIES & IMPROVING CROP PRODUCTION USING DATA MINING TECHNIQUES IN PRECISION AGRICULTURE ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppd642-d650, November-2023, Available at : http://www.jetir.org/papers/JETIR2311379.pdf