IoT to Digital Twin: A Futuristic Smart Farming Akshay M J Department of Information Science and Engineering, Jawaharlal Nehru New College of Engineering and Visvesvaraya Technological University(Belagavi), Shivamogga, India akshaymj@jnnce.ac.in Premasudha B G Department of Master of Computer Applications, Siddaganga Institute of Technology and Visvesvaraya Technological University, (Belagavi) , Tumakuru, India bgpremasudha@sit.ac.in ORCID- 0000-0002-4167-2829 Seema B Hegde Department of Electronics and Communication, Siddaganga Institute of Technology and Visvesvaraya Technological University, (Belagavi) , Tumakuru, India seemab_hegde@sit.ac.in ORCID- 0000-0002-4495-352X Abstract— The global population is rising and there is a need for smartness in agriculture. With the advancement in technology, it is possible to handle agricultural activities in a smart manner. The Internet of Things, Digital Twins, Artificial Intelligence, Machine Learning and Big data can be used for agriculture. Improving the farming efficiency and quality is a major challenge. Most of the day-to-day activities of the farms can be automated and monitored by the farmers. Moreover, there is a need for real-time analysis of the collected data, which can be more informative and realistic and helps in prediction of the future and decision making. The digital twins can be introduced to agriculture, which can help in various activities and making predictions. The digital twins and IoT can be a useful combination for agricultural activities. The various applications, parameters used, and the modeling adopted for digital twins for agriculture is highlighted in this article. Keywords—IoT, Digital Twin, Smart farming I. INTRODUCTION Agriculture is the main source of income for the farmers. Intelligence must be introduced into farming operations. Producing higher quality and increasing output are the primary issues in farming. As the world's population is expected to expand and food consumption is predicted to climb, intelligent farming is becoming more and more important. IoT connects and supports everything. This facilitates all phases of the decision-making process, including selecting the seed, growing the crop, starting a revolution, getting ready, watering, producing, post- yielding, and controlling insects and infections. Farmers can save resources like water and fertilizer and reduce crop wastage with the use of IoT. Increased agricultural yields and lower running costs are the outcomes of this. The Internet of Things (IoT) is a set of systems that allows people, animals, and objects to be uniquely identified and to transmit data over an Internet network without requiring human-to-human or human-computer interaction. The development of IoT in the agriculture sector is one example of how ICT is being applied and how digital transformation is influencing every aspect of human life. In this discipline, energy consumption, data aggregation, wireless transmission, and network maintenance are seen to be the most difficult aspects. In order to possess excellent predictive abilities, data sensing, networking, storage, and processing are the main components of smart agriculture. For better predictive capabilities, data must be examined via multiple algorithms once it has been captured. Though a lot has been developed in the field of smart farming, not much has been developed at the end user (implementation) level. II. REVIEW The section describes about the usage of IoT and other technologies in farming activities. An IoT framework for food and farm systems [1] for the Business Process Hierarchy view of the different use case is presented. The domain model view point, business process view point, IoT layer view point, information model view point, deployment view point, interoperability view point are discussed. The process includes placing the physical entities, control and sense, Data Collection, Data Analysis, Monitor, Decide. An IoT system for ecological monitoring, precision agriculture is used [2]. The platform can be implemented using different server platforms and cloud technologies. Use case considered includes Smart Irrigation system, Soil fertilization and Spraying, Disease forecasting detection. Adoption challenges of IoT technology in the Agricultural and Food Supply Chain are discussed [3]. The various factors and types of agriculture are discussed, which includes greenhouse precision agriculture, tracking, machinery for agriculture, monitoring are included. An overview of 5G in agriculture is provided, together with information on its prospects and challenges [4]. High data transmission volumes and low latency made possible by 5G deployment can have a positive impact on agri-food technology applications like Blockchain and IoT. Data driven platform [5] and IoT for agriculture is discussed. In order to properly duty cycle various base station components, it makes advantage of weather forecasts. A PC at the farmer's house acts as a gateway for the farm data in the Agro-gain, which has a gateway-based design. Deployment of IoT [6] for protected cultivations is discussed. The temperature and humidity of a commercial- sized greenhouse in Mexico were monitored for six months during the construction, experimental testing, and validation phases of the IoT system. A data-driven predictive model for greenhouse microclimate conditions is being considered. Sigfox network service is used. A low cost IoT based smart farming [7] which supports the plug-and-play nodes approach is included. The change point detection method and the protocol for network clustering are the foundation of the system. This technology helps to enhance decision-making by supporting data processing and monitoring in almost real-time. Timely surveys of factors like air quality, soil moisture content, and ambient temperature are conducted via heterogeneous wireless sensor nodes. Periodically, generated data is sent to the appropriate cluster heads. 2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES) | 979-8-3503-6404-0/24/$31.00 ©2024 IEEE | DOI: 10.1109/ICSSES62373.2024.10561335 Authorized licensed use limited to: SIDDAGANGA INSTITUTE OF TECHNOLOGY. Downloaded on June 24,2024 at 05:56:53 UTC from IEEE Xplore. Restrictions apply.