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India is a country that depends on agriculture, where about half the population relies heavily on agriculture for their livelihood. However, most of the practices undertaken in the agricultural process are not for profit and yield favorable. It should upgrade with current technologies to boost seed quality, check soil infertility, check the water level, environmental changes, and market price prediction, and achieve in agriculture sensitivity of faults and background understanding. The advancement in technology and developments is seen as a significant aspect in their financial development and agricultural production growth. The Internet of Things (IoT), Wireless Sensor Networks (WSN), and data analytics accomplish these upgrades. These technologies help in providing solutions to agricultural issues such as resource optimization, agricultural land monitoring, and decision-making support, awareness of the crop, land, weather, and market conditions for farmers. Smart agriculture is based on data from sensors, data from cloud platform storage and data from databases, all three concepts need to be implemented. The data are collected from different sensors and stored in a cloud-based back end support, which is then analyzed using proper analytics techniques, and then the relevant information is transferred to a user interface, which naturally supported the decision to conclude. The IoT applications mainly use sensors to monitor the situation, which collects a large size of data every time, so in the case of the Internet of Things (IoT) application, sensors contribute more. Data analytics requires data storage, data aggregation, data processing and data extraction. To retrieve data and information from database, we must use data mining techniques. It acts a significant position in the selection-making process on several agricultural issues. The eventual objective of data mining is to acquire information form data transform it for some advanced use into a unique human-comprehensible format. Big data's role in Agriculture affords prospect to increase the farmers' economic gain by undergoing a digital revolution in this aspect that we examine with precision. This paper includes reviewing a summary of some of the conference papers, journals, and books that have been going in favor of smart agriculture. The type of data required for smart farming system are analyzed and the architecture and schematic diagram of a proposed intelligent farming system are included. It also involves implementing different components of the smart farming system and integrating IoT and data analytics in the smart farming system. Based on the review, research gap, research agendas to carry out further research are identified.
Vikranth et al. (Sat,) studied this question.