Smart Farming (Smart Farming Cycle)
Agriculture was ranked second in the world in 2014, providing more than 13 percent to India's Gross Domestic Product (GDP). It also gives a job to more than 50% of the Indian people. One of India's most varied industries, agriculture contributes to the nation's the social structure, the economics, and culture. The technique and practises applied in the existing agricultural system are inherently flawed. We should pose some study questions about food safety and agricultural output, because by 2050, it's predicted that there will be close to 10 billion people on the planet (Patil et al., 2012). A 60 percent increase in agricultural production is required to accomplish these targets. The old agricultural method is insufficient and inconsistent in achieving this. Furthermore, some specialists are already beginning to incorporate innovations into agricultural practise in an effort to reduce expenses and boost performance (Mohamed et al., 2021). As a result, IoT and data analytics are important in agriculture, resulting in innovations like wireless sensor networks (WSNs) (Navarro, Costa, and Pereira, 2020; Ouafiq et al., 2021; Vikranth, 2021). IT agriculture, often known as smart farming, is the practise of using technological breakthroughs and worldwide networking to help agricultural solve issues methodically. In this scenario, sensors are particularly crucial since they collect a variety of crop-related data, including moisture, pest, and weather information, as well as information about the soil, water levels, and fields. A number of sensors, including moisture sensors, electromagnetic sensors, and optical sensors, must be employed to gather all of this data. Large amounts of data are produced by sensor-enabled devices, which can be stored separately or in a cloud database (Vikranth, 2021).
In order to offer effective answers for several agriculture applications, the wireless sensor network (WSN) integrates sensor interpretation, mechanization management, digital network transmission, data storage, and data dispensation (Rajasekaran & Anandamurugan, 2019). By utilizing wireless sensor networks, precision agriculture would increasing efficiency, output, and revenue of diverse farming production methods (WSNs) (Sanjeevi, 2020). IoT aids farmers by providing real-time updates by informing the public about their crops using the wireless network. Various sensors, including temperature, moisture, and water level sensors, and flood gauge sensors, can be connected (Vikranth, 2021). With the help of these many sensors, the farmer can receive conscious notifications on what is going on in the field (Veena, 2018). As wireless communication technology develops, short-range communication is made possible by compact, multipurpose sensors with low power requirements and cheaper costs.
The management of farms utilising robotics, drones, artificial intelligence (AI), and the Internet of Things (IoT) is known as “smart farming,” and it aims to boost product quantity and quality while lowering the need for human labour (Navarro, Costa, and Pereira, 2020). Utilizing information and technology, smart farming solutions optimize farming inputs and procedures along the food supply chain, including transportation, distribution, and retail, in order to increase crop and livestock production's economic yield. Cyber systems that enable monitoring, intelligent forecasts, decision assistance, automated control, and long-term planning are among the technologies that rely on big data analytics (Wolfert et al., 2017; Lokhorst, De Mol, and Kamphius, 2019). In order to increase the economic yield of crop and livestock production as well as to optimize farming inputs and procedures along the entire food supply chain, including transportation, distribution, and retail, smart farming solutions leverage information and technology. Cyber systems that enable monitoring, intelligent forecasts, decision support, automated control, and long-term planning are among the technologies that depend on big data analytics (Sarker et al., 2020; Lokhorst, De Mol, and Kamphius, 2019).
The IoT-based smart farming lifecycle: The data you can extract from devices and send over the internet is the basis of the Internet of Things (IoT) (Ruan et al., 2019; Verdouw et al., 2021). IoT devices installed on farms should gather data and process it repeatedly so that farmers can react quickly to emerging problems and changes in the environment. This will optimize the agricultural process. This cycle is used in smart farming as figure 1.
- 1.
Observation . Sensors capture observational data from the atmosphere, soil, livestock, and/or crops.
- 2.
Diagnostics. The sensor data is sent to an IoT platform located in the cloud that has predefined decision rules and models, often known as “business logic,” that determine the status of the object being studied and pinpoint any needs or inadequacies.
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Decisions . After problems are identified, the user and/or machine learning-driven IoT platform components decide whether location-specific therapy is required and, if so, which treatments should be used.
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Action. Once end users have evaluated and taken action, the cycle resumes (Sciforce, 2021).