Applicability of UAVs in detecting and monitoring burning residue of paddy crops with IoT Integration: A step towards greener environment

• Published in: Computers & industrial engineering 2023-10, Vol.184, p.109524, Article 109524
• Main Authors: Sharma, Amit, Kumar Singh, Pradeep
• Format: Article
• Language: English
• Subjects: Agriculture; Alternate Energy Methods; Climate Change; Machine learning; Paddy crops; Sustainable Environment; Unmanned aerial vehicles (UAVs); Waste Management
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2023.109524

•Article promotes sustainable agricultural waste utilization for bioenergy development.•Study proposes combining the Prediction and Monitoring Model (PMM) with picture’s classification for improved burning residue detection.•Improved burning residue recognition using PMM and picture’s classification in real-time aerial data.•CNN-based approach is used for image classification, PMM for effective detection and monitoring of burning residue detection.•Paper analyses residue management techniques and site-specific technology considering socioeconomic factors. The disposal of paddy-based residue in some parts of Indian north-western states, particularly in Punjab and Haryana, has emerged as a significant issue, leading farmers to resort to on-site burning. This practice wastes valuable resources, has detrimental effects on the local economy, and poses a global environmental challenge. The consequences of burning agricultural residues include soil erosion, carbon sequestration problems, and a negative impact on the ecosystem. Recognizing the importance of managing paddy residue due to its nutrient content and its contribution to soil–plant-atmosphere continuity, this article aims to quantify the amount of residue generated and shed light on the adverse effects of residue burning on human health, soil quality, and the environment in the region. Employing drone technology, the study presents an experimental case based on data collected from selected states in India. Real-time monitoring of agricultural land using unmanned aerial vehicles (UAVs) enables the acquisition of crucial data on paddy residue. The collected images are then transferred to the cloud for analysis and decision-making purposes. By leveraging this approach, the study achieves an accuracy of 96.67% in analysing paddy crop waste and identifying areas where residue burning occurs. The proposed work offers timely assistance to state authorities in pinpointing burning locations promptly, and taking necessary measures accordingly. This monitoring initiative not only contributes to climate control efforts but also aids in combating the rising AQI levels of air pollution, and potentially exploring other means of monitoring various environmental factors.