Heena T. Shaikh*,
Kazi Kutubuddin Sayyad Liyakat,
- Assistant Professor, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
- Professor and Head, Department of Electronics and Telecommunication Engineering, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India
Abstract
The integration of Internet of Things (IoT) technology into precision agriculture has transformed pesticide application strategies, enabling resource-efficient and environmentally sustainable practices. This study presents a computational methodology for optimizing pesticide requirements in an IoT-operated hexacopter system, designed for dynamic, data-driven pesticide delivery. Leveraging a fusion of real-time telemetric data from onboard LiDAR, multispectral imaging sensors, and environmental monitoring modules, the system employs predictive analytics and edge computing to calculate precise pesticide dosages. A bespoke algorithm, incorporating crop-specific parameters (e.g., canopy density, pest infestation hotspots), field geometries, and weather volatility (humidity, wind velocity), generates a spatiotemporal pesticide distribution model. The hexacopter autonomously adjusts spray patterns and dosage rates via closed-loop feedback, minimizing over-application and drift while targeting affected zones with sub-meter resolution. Field trials demonstrated a 38% reduction in pesticide usage compared to conventional methods, alongside a 25% improvement in pest control efficacy. The system’s adaptive recalibration mechanism, driven by machine learning–enhanced predictive models, ensures scalable deployment across heterogeneous agricultural landscapes. This work underscores the potential of IoT-enabled aerial platforms to harmonize agricultural productivity with ecological stewardship through algorithmic precision in resource allocation.
Keywords: Dosage, Hexacopter, IoT, pesticide, spray patterns
[This article belongs to International Journal on Drones ]
Heena T. Shaikh*, Kazi Kutubuddin Sayyad Liyakat. Optimization of Pesticide Requirement Calculations for IoT-Operated Hexacopter Delivery Systems. International Journal on Drones. 2026; 02(01):08-14.
Heena T. Shaikh*, Kazi Kutubuddin Sayyad Liyakat. Optimization of Pesticide Requirement Calculations for IoT-Operated Hexacopter Delivery Systems. International Journal on Drones. 2026; 02(01):08-14. Available from: https://journals.stmjournals.com/ijd/article=2026/view=239857
References
- S, R. Chinnaiyan and C. Kalaiarasan, “IoT Based Connected Agro Plant Using Drones and Block Chain,” 2022 7th International Conference on Robotics and Automation Engineering (ICRAE), Singapore, 2022, pp. 426-430, doi: 10.1109/ICRAE56463.2022.10056171.
- Bencini, F. Chiti, G. Collodi, D. Di Palma, R. Fantacci, A. Manes, G. Manes. “Agricultural Monitoring Based on Wireless Sensor Network Technology: Real Long-Life Deployments for Physiology and Pathogens Control,” Sensor Technologies and Applications. SENSORCOMM ’09. Third International Conference on, 2009.
- R. Chinnaiyan, M.S. Nidhya ( 2018 ), “Reliability Evaluation of Wireless Sensor Networks using EERN Algorithm ”, Lecture Notes on Data Engineering and Communications Technologies, Springer International conference on Computer Networks and Inventive Communication Technologies (ICCNCT – 2018), August 2018 (Online).
- R. Chinnaiyan, S. Balachandar ( 2018 ), “Centralized Reliability and Security Management of Data in Internet of Things (IoT) with Rule Builder ”, Lecture Notes on Data Engineering and Communications Technologies, Springer International conference on Computer Networks and Inventive Communication Technologies (ICCNCT – 2018), August 2018 (Online).
- R and Dr. R. Chinnaiyan, “Reliable Constrained Application Protocol to Sense and Avoid attacks in WSN for IoT Devices,” 2019 International Conference on Communication and Electronics Systems (ICCES), Coimbatore, India, 2019, pp. 1898–1901.
- R. Chinnaiyan, S. Balachandar ( 2018 ), “Centralized Reliability and Security Management of Data in Internet of Things (IoT) with Rule Builder ”, Lecture Notes on Data Engineering and Communications Technologies, Springer International conference on Computer Networks and Inventive Communication Technologies (ICCNCT – 2018), August 2018 (Online).
- S. Nirmala, R. Chinnaiyan ( 2021 ). Blockchain based Secured Framework for Road Traffic Management using Fog Computing. International Journal of Computational Intelligence in Control 13 ( 2 ).
- Sabarmathi and Dr. R. Chinnaiyan, “Big Data Analytics Framework for Opinion Mining of Patient Health Care Experience ” International Conference on Computing Methodologies and Communication (ICCMC 2020), IEEE Xplore Digital Library.
- Hari Pranav A ; M. Senthilmurugan ; Pradyumna Rahul K ; R. Chinnaiyan, “IoT and Machine Learning based Peer to Peer Platform for Crop Growth and Disease Monitoring System using Blockchain,” 2021 International Conference on Computer Communication and Informatics (ICCCI), 2021, pp. 1–5, doi: 10.1109/ICCCI50826.2021.9402435.
- A. Tamboli, V. A. Sawant, M. H. M. and S. Sathe, (2024). AI-Driven-IoT(AIIoT) Based Decision-Making- KSK Approach in Drones for Climate Change Study, 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS), Gobichettipalayam, India, 2024, pp. 1735-1744, doi: 10.1109/ICUIS64676.2024.10866450.
- (2025). AI-Driven-IoT (AIIoT)-Based Decision Making in Drones for Climate Change: KSK Approach. In S. Aouadni& I. Aouadni (Eds.), Recent Theories and Applications for Multi-Criteria Decision-Making (pp. 311-340). IGI Global. https://doi.org/10.4018/979-8-3693-6502-1.ch011
| Volume | 02 |
| Issue | 01 |
| Received | 29/01/2026 |
| Accepted | 26/02/2026 |
| Published | 10/03/2026 |
| Publication Time | 40 Days |
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