Agriculture is increasingly combining traditional farming knowledge with sensors, artificial intelligence (AI) and digital tools to improve crop management and resource use. This emerging approach was the focus of a two-day hands-on workshop on “AI-Powered Precision Agriculture Using Large Language Models (LLMs) and Internet of Things (IoT)”, organised by the Department of Electronics Technology at Guru Nanak Dev University (GNDU).Around 80 students from the Departments of Electronics Technology, Computer Engineering and Technology, and Computer Science participated in the workshop, where they received practical exposure to IoT, sensors, AI, Large Language Models, Retrieval-Augmented Generation (RAG), automation and Agentic AI, with a focus on addressing agricultural challenges.Dr Tarandeep Singh, Scientist, Instrumentation, Punjab Agricultural University, Ludhiana, introduced participants to the use of IoT devices and sensors in precision agriculture. Through practical demonstrations, students learned how sensors can collect information from agricultural environments and support data-driven decision-making.“For Punjab, where agriculture faces growing concerns related to water consumption, resource efficiency and sustainable farming, precision agriculture offers an important technological pathway,” he said. A key focus of the session was the judicious use of natural resources, particularly water. Instead of applying resources uniformly across an entire field, sensor-based systems can help identify variations in field conditions and enable more targeted interventions.Jagpal Singh, Data and AI Governance Engineer at Komatsu Australia, conducted brainstorming and hands-on sessions on Large Language Models and their potential applications in agriculture. Participants were introduced to AI-powered agricultural chatbots and Retrieval-Augmented Generation (RAG), which enables AI systems to work with specialised and trusted information alongside their general training. The session also introduced the Open Knowledge Format (OKF) and discussed its potential for developing intelligent, domain-specific agricultural applications.Participants were also introduced to initiatives such as ANNAM.AI at IIT Ropar, which focuses on developing agricultural intelligence systems and has explored applications including AI-powered weather stations and hyperlocal agricultural information.Nikhil Sharma, AI Consultant, Beghou, Bengaluru, took participants from the fundamentals of LLMs to more advanced applications. Students worked with AI platforms and models and gained practical exposure to agriculture-focused use cases.The workshop also covered emerging technologies, including Model Context Protocol (MCP), AI automation workflows, Agentic AI and the attention mechanism. Nikhil Sharma said future agricultural systems could potentially combine information from sensors, databases and other digital sources to help farmers make increasingly complex and context-specific decisions.Dr Hardeep Kaur, Head of the Department of Electronics Technology, GNDU, said the programme brought students from electronics and computing disciplines onto a common platform. “This interdisciplinary approach is particularly relevant to Agri-Tech, where the future of farming will depend on the convergence of hardware, connectivity, data and intelligence,” she said.She added that students were not merely learning about IoT and AI but were being encouraged to explore how these technologies could be combined to address problems specific to Punjab’s agricultural ecosystem.