Abstract: This tutorial introduces participants to the fundamentals of using drone technology to capture and process aerial imagery for agricultural applications. It aims to equip attendees with the knowledge and tools necessary to acquire, analyze drone-captured images to monitor crop health, predict crop stress, and monitor farm yields. The session will cover key aspects such as drone operation, image capturing techniques, and advanced data analysis methods. Participants will learn how to interpret NDVI indices, and make informed decisions based on real-time data. This tutorial is designed for beginners and intermediate users who wish to integrate drone technology into their agricultural practices to achieve sustainability and efficiency. By the end of this tutorial, attendees will be able to effectively deploy drones, process imagery, and apply insights to their farming strategies.
Speaker: Prof. Shashank Tamaskar, Plaksha University.
Abstract: Food security has grown into a serious concern in all countries around the globe due to the growing population, the depletion of renewable resources, the loss of agricultural farmlands, as well as the rise in uncertain weather conditions. Precision farming is an emerging technology to measure, monitor, and analyse the demands of particular fields and crops. The primary goal of this farming method, compared to conventional farming, is to maximize crop yield and profitability, management of soil and crop, that improve knowledge and control of spatial and temporal variability to lower decision uncertainty. With varying degrees of success, a lot of study has been done to create techniques for crop management that are particular to a given location in various agricultural systems. These applications only relied on variable rate technology to control spatial variation at the sub-field level and have frequently fallen short of achieving appreciable and sustained gains in agricultural yields, profitability, input efficiency, and environmental impact. With increasing the food demand, the agricultural industry is shifting to "smart agriculture," which makes use of artificial intelligence (AI) and the Internet of Things (IoT) to streamline processes and boost output. IoT and AI incorporate several cutting-edge methods and technologies, such as big data, cloud computing, networking, sensor technology, and end-user apps. Precision agricultural technologies are becoming increasingly associated, precise, efficient, and broadly applicable due to technological advancements and big data innovations. Enhancements to the technological infrastructure and regulatory framework can potentially increase the scope of precision farming, thereby increasing its total benefits to society. The machines gradually replaced labour, crop yields spiked, and the economy was attained with the extensive automation of the farming sector in the twentieth century. With precision agricultural methods, crops may be produced for maximum productivity in a given location at a specific time of year, regardless of the prevailing agro-climatic conditions. The cost of cultivation is determined by the discrepancy between the microclimatic characteristics of the crop and the surrounding climate. To maximize productivity while consuming the least amount of energy and time, precision application approaches would offer rapid and safe large-scale classification with the advantages of instantaneous data availability, flexibility, ease of operations, and particular spatial precision. These emerging technologies that provide reliable and effective solutions for the automation of agriculture and related industries. IoT-based systems that monitor agricultural productivity and the environment remotely with little human involvement are being built using sensor technologies. The firm is starting to attract suppliers and farmers alike as it moves into more remote areas. In addition to making farmers' lives simpler, the use of IoT and AI technologies in protected cultivation may assist researchers in developing alternative prediction models for the precise scheduling of vital resources. Presently, efforts have been made to establish more comprehensive, dynamic, and integrated types of site-specific management. This study aims to investigate recent advancements in smart applications that leverage IoT and AI technologies for precision agriculture. In addition to highlighting the trends and opportunities in this area, it also draws attention to the unresolved issues and challenges related to smart applications in smart agriculture. Additionally, this research will contribute to the understanding of how applications of AI and IoT may be integrated into the smart agriculture sector. Precision farming will be extremely helpful in future research and development of IoT and AI technologies aimed at improving the agricultural sector's profitability and quality standards.
Keywords: Precision farming, Smart agriculture, Sustainable production, Internet of Things, Artificial Intelligence
Speaker: Anamika Yadav
Abstract: This tutorial introduces problems faced by farmers e.g. Present Automation vs Erratic Electicity, Water level in well/storage, Affordability, Automation during Rain handling, Wiring etc. How more improvements are required in current auomation solutions for precision irrigation?
Hands-on: A Weather monitoring data using sensors e.g Temperature/Humidity will be sent to cloud over HTTP/MQTT Protocoal using Wifi. A dashboard on cloud server will also be used to manange data.
Speaker: Kaushlendra Singh Sisodia, Kaushlendra is an IIT Kanpur Alumni (M.Tech. 2001), presently working as Director at UniConverge Technologies Pvt. Ltd. (UCT). He is the Chief Mentor of The IoT Academy (Skill development and Trainings). He is also the Co-founder of The IoT Academy, UCT Consulting, UCT Robotics, and Upskill Campus. He has 22+ years of work experience in the industry. He has worked with many MNCs such as Ericsson AB, Sweden, STMicroelectronics Pvt. Ltd, Noida, UbiNetics India Pvt Ltd, Bangalore, and SASKEN Communication Tech., Bangalore