Authors : Pranav Shivanand Patil; Prasanna Prasad Shenoy; Pavan YDG; Prajwal Prakash Shetti; Sai Gagan Sirigeri; Shobha T

Volume/Issue : Volume 10 - 2025, Issue 1 - January

Google Scholar : https://tinyurl.com/4m5j4fzj

Scribd : https://tinyurl.com/5hdpwsvn

DOI : https://doi.org/10.5281/zenodo.14724977

Abstract : Artificial Intelligence integrated into Unmanned Aerial Vehicles has transformed data collection for a better cause in ensuring enhanced security, operation efficiency, and accuracy. Based on the literature available, the paper goes ahead to describe recent advances in the quest toward secure and autonomous acquisition techniques making use of drones by underlining state-of-the-art approaches: AI-based decision-making processes, real-time threat detection, and multi-layered encryption protocols. The proposed framework has incorporated the advanced model of machine learning, enabling the drones to navigate through difficult terrains and respond dynamically to environmental changes independently. It has enhanced the security and integrity of the data. Due to AI-driven algorithms, the system will be able to continuously monitor and respond to a possible threat. Real-time anomaly detection thus enables any cyberattack and unauthorized access to the data. Secure encryption and communication channels even further enhance this in high-risk or remote environments, disaster locations, and even zones of conflict. In all such scenarios, critical functions like safe surveillance, mapping, and gathering could be conducted without risking lives when the works are undertaken through UAVs. Integration with blockchain enhances the level of integrity of the information and its traceability with a unique permanent ledger to record data throughout, from creation until delivery. The capability for data verification and auditing in this blockchain component will, therefore, be very important for sectors dealing in sensitive or regulated information. By integrating machine learning into the tamper-proof record-keeping capability of blockchain, the system identifies any unauthorized access or tampering at any stage of operation and thus assures integrity in end-to-end data management. Versatile in their nature, their applications span diversified fields: environmental monitoring, emergency response, border security, where the secure, precise handling of data is essential. These would include industrial areas where drones are able to view hazardous areas like oil spills to offer a much safer and efficient alternative than human intervention could. This paper also considers emerging trends and possible applications that underline how continued technological advancements keep further extending the scope for AI-enabled secure UAV operations both in the public and private

Keywords : Secured Data Collection, Encryption, Machine Learning, Blockchain, Autonomous UAV.

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