Investigating the Use of Drone Technology for Agricultural Crop Monitoring and Management

This paper has examined the application of drone technology across the spectrum of agricultural crop monitoring and management from crop health assessment and irrigation scheduling to precision spraying and yield forecasting. The evidence is compelling: UAV-based systems, when paired with appropriate sensor payloads, processing pipelines, and machine learning analytics, substantially outperform conventional monitoring in speed, coverage, early-detection capability, and long-run cost-effectiveness. The key barriers to scaled deployment hardware cost, battery endurance, data processing overhead, regulatory complexity, and digital literacy gaps are real but addressable through a combination of service-based delivery models, edge computing, simplified advisory interfaces, and progressive regulatory reform. The five-component framework proposed in this paper provides a concrete pathway for translating the demonstrated technical potential of drone-based agriculture into widespread, equitable benefit for Indian farmers, including the smallholder majority who cannot afford direct equipment ownership. For MCA students and computer science researchers, the drone-agriculture intersection represents a rich domain that combines computer vision, geospatial computing, machine learning, embedded systems, and cloud architecture. As drone hardware becomes increasingly commodity and data volumes grow, the dominant value creation will shift further toward software, analytics, and AI territory where the computer science community has a central role to play in shaping the future of food production. The next decade will determine whether precision agriculture technologies remain the preserve of large, well-capitalised farms or become a genuinely democratised tool available to the 85% of Indian farmers who operate holdings smaller than two hectares. Achieving the latter outcome will require not just better technology, but better systems thinking and that is precisely the challenge that interdisciplinary research, of the kind this paper has sought to contribute to, must address.

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