Non-Fungible Tokens (NFTs) have emerged as a revolutionary method for managing digital assets, providing transparency and secure ownership records on a blockchain. In this paper, we present a theoretical framework for leveraging NFTs to manage UAV (Unmanned Aerial Vehicle) flight data. Our approach focuses on ensuring data integrity, ownership transfer, and secure data sharing among stakeholders. This framework utilizes cryptographic methods, smart contracts, and access control mechanisms to enable a tamper-proof and privacy-preserving management system for UAV flight data.
Julio César Úbeda Ortega, Jesús Rodríguez-Molina, Margarita Martínez, Juan Garbajosa
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.
M. Rajesh, T. Archana Acharya, Hafis Hajiyev, E. Laxmi Lydia · 8 authors
Recently, Internet of Things (IoT) has been developed into a field of research and it purposes at linking many sensors enabling devices mostly to data collection and track applications. Wireless sensor network (WSN) is a vital element of IoT paradigm since its inception and has developed into one of the chosen platforms for deploying many smart city application regions such as disaster management, intelligent transportation, home automation, smart buildings, and other such IoT-based application. The routing approaches were extremely-utilized energy efficient approaches with an initial drive that is, for balancing the energy amongst sensor nodes. The clustering and routing procedures assumed that Non-Polynomial (NP) hard problems but bio-simulated approaches are utilized to a recognized time for resolving such problems. With this motivation, this paper presents a new blockchain with Enhanced Hunger Games Search based Route Planning (BCEHGS-RP) scheme for IoT assisted WSN. The presented BCEHGS-RP model majorly employs BC technology for secure communication in the IoT supported WSN environment. In addition, an effective multihop route planning approach was designed by the use of EHGS technique. The proposed EHGS technique is derived from the concept of Hill Climbing strategy (HCS) and HGS algorithm. Moreover, a fitness function with two parameters namely residual energy (RE) and inter-cluster distance to elect optimal routes. The performance validation of the BCEHGS-RP model is experimented with under diverse number of nodes. Extensive experimental outcomes highlighted the better performance of the BCEHGS-RP technique on recent approaches.
Roman Overko, Rodrigo Ordóñez-Hurtado, Sergiy Zhuk, Robert Shorten
In this paper, we describe an approach to guide drivers searching for a parking space (PS). The proposed system suggests a sequence of routes that drivers should traverse in order to maximise the expected likelihood of finding a PS and minimise the travel distance. This system is built on our recent architecture SPToken, which combines both Distributed Ledger Technology (DLT) and Reinforcement Learning (RL) to realise a system for the estimation of an unknown distribution without disturbing the environment. For this, we use a number of virtual tokens that are passed from vehicle to vehicle to enable a massively parallelised RL system that estimates the best route for a given origin-destination (OD) pair, using crowdsourced information from participant vehicles. Additionally, a moving window with reward memory mechanism is included to better cope with non-stationary environments. Simulation results are given to illustrate the efficacy of our system.
Nicolas Dousse, Grégoire Heitz, Felix Schill, Dario Floreano
Semi- or fully autonomous personal aerial vehicles (PAVs) are currently studied and developed by public and private organizations as a solution for traffic congestion. While optimal collision-free navigation algorithms have been proposed for autonomous robots, trajectories and accelerations for PAVs should also take into account human comfort. In this letter, we propose a reactive decentralized collision avoidance strategy that incorporates passenger physiological comfort based on the optimal reciprocal collision avoidance strategy. We study in simulation the effects of increasing PAV densities on the level of comfort, on the relative flight time and on the number of collisions per flight hour and demonstrate that our strategy reduces collision risk for platforms with limited dynamic range. Finally, we validate our strategy with a swarm of ten quadcopters flying outdoors.
Decentralized control methods are appealing in coordination of multiple vehicles due to their low demand for long-range communication and their robustness to single-point failures. In this paper we explore a decentralized approach to path generation for a group of vehicles in a battlefield scenario. The mission is to maneuver the vehicles to cover a target area while avoiding obstacles and threats during the maneuver. Each vehicle makes its moving decision by minimizing a potential function that encodes information about its neighbours, obstacles, threats and the target. Preliminary analysis of vehicle behaviors is conducted. Simulation has shown that this approach leads to interesting emergent behaviors, and the behaviors can be varied by adjusting the weighting coefficients of different potential function terms.
Toshio Fukuda, Go Iritani, Fumihito Arai, Koji Yamada
In this research, we address the organization of group behavior on decentralized autonomous robotic systems. Collective group behavior is exhibited in the natural world, such as by ants and fish, in teamwork in sports and by the human society. Therefore, research on group behavior of decentralized autonomous robotic systems can be regarded as one the research fields of Artificial Life. Decentralized autonomous robotic systems refer to multiple robotic systems including many autonomous robots, such as the Cellular Robotic System (CEBOT). The CEBOT, which has been studied by the authors, consists of a number of robotic units called cells. In research on the CEBOT, it is necessary to evolve a cooperative group behavior effectively in the system, since a well-organized group behavior is required to carry out given tasks efficiently and influences its performance ability. In order to organize the behavior in a dynamic environment, we proposed a concept of the self-recognition for the decision making of the behavior in a robotic group. In addition to the proposed concept, this paper will show a construction mechanism of group behavior using the character of the attractor. Based on this idea, we present the behavioral evolution of a group robotic system.
In this research, we address the organization of group behavior on decentralized autonomous robotic systems. Collective group behavior is exhibied in the natural world, such as by ants and fish, in teamwork in sports and by the human society. Therefore, research on group behavior of decentralized autonomous robotic systems can be regarded as one of the research fields of Artificial Life. Decentralized autonomous robotic systems refer to multiple robotic systems including many autonomous robots, such as the Cellular Robotic System (CEBOT). The CEBOT, which has been studied by the authors, consists of a number of robotic units called "cells". In the research on the CEBOT, it is necessary to evolve a cooperative group behavior effectively in the system, since a well-organized group behavior is required to carry out given tasks efficiently and influences its perfor-mance ability. In order to organize the behavior in a dynamic environment, we proposed a concept of "self-recognition" for decision making of the behavior in a robotic group. In this paper, in addition to the proposed concept, we will show the organization and adaptation of group behavior with the coordination of intention, and represent some simulation results with the coordination of intention.