A Proposal for Decentralized and Secured Data Collection from Unmanned Aerial Vehicles in Livestock Monitoring with Blockchain and IPFS

Featured Application The presented work makes significant contributions towards setting the technologies, both in terms of hardware and software, required for the usage of Unmanned Aerial Vehicles in livestock monitoring in a secure, decentralized manner. Thus, secure livestock management, animal behaviour data collection or cattle tracking throughout a specific period are but a few of the applications that the proposed system can support. Livestock monitoring often requires human supervision to guide farm animals to a specific point and the displacement of workers to the places where these animals are, which is likely to be several kilometers away, thus resulting in a repetitive task that requires a significant amount of time and demands the usage of land vehicles capable of moving swiftly through the countryside. In addition to that, data collection about animal behaviour with such procedures is often insufficient and cannot be shared in a secure enough manner. This paper describes how Using Unmanned Aerial Vehicles (UAVs) tailored for this kind of task, when combined with other protocols and software technologies, can provide a useful to mitigate these issues. To prove this end, a functional prototype has been designed, built and tested, offering the operator accurate monitoring of farm facilities and animals. Additionally, security has been conceived as a cornerstone of the presented system from the very beginning. Not only the communication protocols used for this purpose have built-in security layers, but also InterPlanetary File System (IPFS) and blockchain have been used as the technologies that enhance data storage among peers in a network.

Automated summary

This paper presents how to use UAVs and other protocols and software technologies to achieve a secure livestock monitoring system, addressing the issues of manual operation and data sharing in traditional livestock monitoring.