Swarm Intelligence Based Drones: Opportunities & Future Aspects (original) (raw)
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Formation of a Wireless Communication System Based on a Swarm of Unmanned Aerial Vehicles
Information and Telecommunication Sciences
Background. Currently, a new direction in the technology of mobile systems is rapidly developing, associated with the use of a set / group of mobile multifunctional elements that can create different spatially-distributed structures for various applications: from entertainment shows to intelligence networks. This is a technique of small unmanned aerial vehicles (UAV), often called drones, and their use in the field of building telecommunication systems. Objective. The aim of the work is to develop the basic principles and strategies for the formation of a heterogeneous wireless communication system based on a swarm of unmanned aerial vehicles. Methods. We study the structural and functional methods of building a wireless network. Results. Scenarios of centralized and distributed building of a wireless network of control of a swarm of UAVs are presented, assessment of the complexity of the functionality of swarm nodes in the case of a distributed scenario is carried out. A scheme of phased implementation of the life cycle of a UAV swarm for communication services has been developed. The "molecular" scenario of spatial self-organization of the swarm-nodes of the swarm is presented, which can be implemented using the "chain" and "flash" procedures. The proposed construction of some strategies for managing the swarm: centralized and decentralized with the Leader, collective self-management with information sharing, decentralized management with forecasting, self-organization without information sharing. Conclusions. The basic principles and strategies for the formation of a heterogeneous wireless communication system based on a swarm of unmanned aerial vehicles have been developed. A collective management strategy for a swarm of drones was developed.
Review paper on connecting the dots using drones
International Journal of Advance Research, Ideas and Innovations in Technology, 2020
From the past few years, drones have been a trending topic surrounding technology. There are many applications leading to the advancement of the drones such as aerial photography as well as videography, shipping and delivery, geographic mapping, disaster management, precision agriculture, search and rescue operations, weather forecast, wildlife monitoring, law enforcement, and many more. In a country like India, drones will play a vital role in dealing with problems from the front. A Drone with the latest technology onboard will be able to change the downgraded frame of India. Like a drone with a medical kit will give higher efficiency in reachability, remote farming will be smoothly operated using a drone, from a military point view it will be helpful in guarding the hilly posts over LOC, etc. Thus if the future technology implemented as soon as possible in India it will provide huge latency.
A new approach to realize drone swarm using ad-hoc network
2017 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), 2017
Swarms of drones are increasingly being requested to carry out missions that cannot be completed by single drones. Particularly in the field of civil security, strong needs emerge in terms of surveillance and observation of hostile, distant or extended areas. Currently, existing solutions do not meet this demand, as they are generally based on too heavy infrastructures or over-processing, without consideration of quality of service (especially in terms of throughput). In this paper, we propose a light and efficient solution to synchronize and orchestrate a swarm of drones, based only on ad hoc communications to position drones. Our proposal operates a swarm by human piloting a drone (the leader), while all the others (the followers) are completely autonomous and follow the leader using Wi-Fi signal strength. We provide algorithms to realize a basic line scenario. Based on two software developed in the framework of this work, real flight tests have been conducted and experiment results are shown.
Wireless and Satellite Systems, 2018
The use of unmanned aerial systems is increasingly common in both research and industrial fields. Nowadays, the use of single unmanned aerial vehicles is quite established and several products are already available to consumers, while swarms are still subject of research and development. This work describes the objectives of a research project, namely SCIADRO, which deals with innovative applications and network architectures based on the use of single unmanned aerial vehicles and of swarms in several civilian fields.
Artificial Intelligence (AI) of drone swarms depends on reliable communications. The parallelism and distributed characteristics of swarm intelligence provide self-adapting and reliable capabilities. This article is devoted to the calculation of packet losses and the impact of traffic parameters on the data exchange in swarms. Original swarm models were created with the help of MATLAB and NetCracker packages. Dependences of data packet losses on the transaction size are calculated for different drone number in a swarm using NetCracker software. Data traffic with different parameters and statistical distribution laws was considered. The effect of different distances to drones on the base station workload has been simulated. Data transmission in a swarm was studied using MATLAB software depending on the signal-to-noise ratio, nonlinearity levels of base station amplifier, signal modulation types, base station antenna diameters, and signal phase offsets. The data obtained allows forese...
Drone swarm technology as a competitive alternative to traditional aerial firefighting
Imprensa da Universidade de Coimbra eBooks, 2022
Aerial firefighting is effective however very expensive solution to suppress forest fires. Drone application as a most developing branch of the aviation industry can be a complement, or perhaps even a competitive solution with the traditional aerial firefighting. Based on the input data drone swarm technology can be not just an effective but also an efficient solution suppressing forest fires. In this study author used both practical and theoretical approach to investigate the possibility of drone usage delivering suppressant to fire front. Firstly, the required width of wetting strip and the required amount of water per unique area were investigated; practical experience shows that based on the flame length first responders can estimate both the effective width of the fire brake and the amount of water required per a unique area. As a second part of this paper, the transport capability of a drone was investigated during its life cycle that is specially optimized for firefighting. In the example author took a 100 kg transport capacity that is easy to transfer to other drone design; in case of 0.3 MWm-1 fire intensity 100 kg water is enough to make 100 m long fire brake, in case of 3.4 MWm-1 fire intensity 100 kg water enough to create only 2.5 m fire brake. Even if this latest results can be seen a bit short we have to take into account the swarm technology. In 10 km distance 30 drones can built a 5 m long fire brake per a minute that means 300 m per hour. This result is no worse than what large or very large air tankers can built averagely in this fire intensity. Expecting the technological development in the near future the length of the fire brake will raise drastically meaning that drone swarm technology will be not a complement but a competitive solution to the traditional aerial firefighting.
A Drones Optimal Path Planning Based on Swarm Intelligence Algorithms
Computers, Materials & Continua, 2022
The smart city comprises various interlinked elements which communicate data and offers urban life to citizen. Unmanned Aerial Vehicles (UAV) or drones were commonly employed in different application areas like agriculture, logistics, and surveillance. For improving the drone flying safety and quality of services, a significant solution is for designing the Internet of Drones (IoD) where the drones are utilized to gather data and people communicate to the drones of a specific flying region using the mobile devices is for constructing the Internet-of-Drones, where the drones were utilized for collecting the data, and communicate with others. In addition, the SIRSS-CIoD technique derives a tuna swarm algorithm-based clustering (TSA-C) technique to choose cluster heads (CHs) and organize clusters in IoV networks. Besides, the SIRSS-CIoD technique involves the design of a biogeography-based optimization (BBO) technique to an optimum route selection (RS) process. The design of clustering and routing techniques for IoD networks in smart cities shows the novelty of the study. A wide range of experimental analyses is carried out and the comparative study highlighted the improved performance of the SIRSS-CIoD technique over the other approaches.
Development of Self-Synchronized Drones’ Network Using Cluster-Based Swarm Intelligence Approach
IEEE Access, 2021
Timing synchronization has a vital role in swarm drones' network (SDN) or a swarm of unmanned aerial vehicle (UAV) network. Current timing synchronization methods focus on enhancing single-hop skews which remarkably improve timing synchronization precision at this level. The improper clock of the drone system can cause interference, affect spectrum precision and interrupt the operation of the transceiver. In the drones' network, master drones' (MD) neighbor drone's timing synchronization approaches like Reference Broadcast System (RBS) realize a good performance. However, the requirement of one super drone with a large number of broadcasts for RBS makes it unrealistic to use in some situations like SDN network situation. Appropriate study and adjustments are needed to have real timing synchronization by eliminating the clocks drift and enhancing the timing synchronization precision. Therefore, a new self-timing synchronization approach is proposed in this paper where several MD drones can autonomously generate swarm clusters. The cluster head (CH) instigates a timing synchronization procedure starting with intra-Swarm cluster timing synchronization. The intermediate drones (ID) are elected between two swarm clusters to synchronize all drones in line with the inter-swarm cluster timing synchronization approach. The proposed approach is distributed and flexible to achieve high timing synchronization precision. The paper proposes a novel self-timing synchronization approach for in large scale semi-flat SND network architecture. Self-timing synchronization is swarm cluster-based and applicable for a huge number of master drones in SDN. One is the intra-Swarm cluster where the timing synchronization procedure starts with the CH to synchronize all CM. Secondly, in the inter-swarm cluster timing synchronization, two clusters are synchronized via intermediate drone (ID). However, the simulations demonstrated that in many cases all CHs are synchronized by the synchronized CHs from intra-swarm cluster timing synchronizations; this increased the system throughput and synchronization delay to about 75% compared to what we planned to achieve. Moreover, the simulation results also proved that the achieved synchronization precision can be used for position estimation and prediction with high accuracy. INDEX TERMS Drones' network, timing synchronization, unmanned aerial vehicle (UAV), cluster, swarm.
Improvement of Emergency Communication Systems Using Drones in 5G and Beyond for Safety Applications
Drones are used for public safety missions because of their communication capabilities, unmanned mission, flexible deployment, and low cost. Recently, drone-assisted emergency communication systems in disasters have been developed where instead of a single large drone, flying ad hoc networks (FANETs) are proposed through clustering. Although cluster size has an impact on the proposed system's performance, no method is provided to effectively regulate cluster size. In this paper, optimum cluster size is obtained through two distinct meta-heuristic optimization algorithms - the Cuckoo Search Algorithm (CUCO) and the Particle Swarm Algorithm (PSO). Flowcharts and algorithms of CUCO and PSO are provided. A presentation of an analytical investigation based on the Markov chain model is provided. To further validate the analytical study, simulation results are presented. Simulation shows the improvement in terms of throughput and packet dropping rate (PDR).
Constraint-based Formation of Drone Swarms
2022
Drone swarms are required for the simultaneous delivery of multiple packages. We demonstrate a multi-stop drone swarm-based delivery in a smart city. We leverage formation flying to conserve energy and increase the flight range of a drone swarm. An adaptive formation is presented in which a swarm adjusts to extrinsic constraints and changes the formation pattern in-flight. We utilize the existing building rooftops in a city and build a line-of-sight skyway network to safely operate the swarms. We use a heuristic-based A* algorithm to route a drone swarm in a skyway network.