| Volume: 8; Issue: 1; June 2026 |
|---|
| Title : AI-DRIVEN DEVICES IN CLIMATE-RESILIENT AGRICULTURE AND SUSTAINABLE FOOD SYSTEMS: LEVERAGING MACHINE LEARNING AND IoT FOR FUTURE-READY INNOVATIONS |
| Authour(s): Nishat Fatima |
| Keywords: Agri-tech innovation, AI, Climate-resilient agriculture, Digital agriculture, Farming, IoT, ML. |
| Abstract: Global agriculture and food security face significant challenges due to climate change, necessitating innovative and long-term solutions. When integrated with machine learning (ML) and the Internet of Things (IoT), AI-powered technologies can revolutionize the development of sustainable food systems and climate-resilient agriculture. Precision farming techniques that maximize resource use while reducing environmental effects, real-time monitoring of soil, water, and crop health, and predictive analytics for weather and yield forecasts are all made possible by these technologies. Big datasets are generated by IoT-enabled sensors, and ML models analyze them to create useful information for adaptive decision-making. Resilience to climatic variability and disruptions is strengthened through applications like supply chain optimization, advanced pest monitoring, and regulated watering. AI-driven technologies create opportunities for agricultural systems that are prepared for the future by increasing productivity, reducing waste, and encouraging environmentally sustainable practices. To ensure sustainability, resilience, and food security, this review article explores how AI, ML, and IoT could be integrated into agriculture. |
| DOI: https://doi.org/10.46505/IJBI.2026.8111 |
| How to cite this article: Fatima Nishat (2026). AI-Driven devices in climate-resilient agriculture and sustainable food systems: Leveraging machine learning and IoT for future-ready innovations International Journal of Biological Innovations. 8(1): 103-113. https://doi.org/10.46505/IJBI.2026.8111 |
Pages: 103-113 | Viewed: 26 | Downloaded: 45| Download: PDF (2771KB) |
