A low-cost physical location discovery scheme for large-scale Internet of Things in smart city through joint use of vehicles and UAVs

Teng, Haojun; Dong, Mianxiong; Liu, Yuxin; Wang, Tian; Liu, Xuxun

doi:10.1016/j.future.2021.01.032

Cited by 39 publications

(7 citation statements)

References 25 publications

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“…If the trash can is full, the sensor will send a signal. After that, the central processing module will obtain the specific location of the trash can through the satellite positioning system and schedule the garbage transport vehicle for garbage handling tasks [56]. GPS can also locate each garbage truck in real-time, thereby reducing the waste of transportation costs.…”

Section: Evolutionary Game Processmentioning

confidence: 99%

Evolutionary Game Analysis of Non-Governmental Organizations Participating in Garbage Management under the Background of Internet of Things

Cui

et al. 2022

Sustainability

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In the context of the information age, due to the development trend of information technology and the increasingly prominent position of economic activities, Internet of Things technology, as an important part of the new generation of information technology, stands out in the management of municipal solid waste collection and transportation management. At the same time, it has also become an efficient management means to realize waste treatment and construct high-quality urban green infrastructure in the environmental protection industry. Under this reality, environmental non-governmental organizations are becoming increasingly important as an organized social force in limiting national environmental power. It has become a crucial force in municipal solid waste management. Within this context, this study aimed to evaluate the strategic choice relationship among environmental non-governmental organizations, local governments, and garbage disposal enterprises, as well as the impact of environmental non-governmental organizations participating in the supervision of the implementation of information waste classification and management systems. In this study, the game theory method is used to construct the tripartite evolutionary game model of local governments, garbage disposal enterprises, and environmental non-governmental organizations, and the Matlab simulation model is established. The results of model analysis and simulation show that direct supervision, financial support, and punishment from non-governmental organizations, as well as pressure measures by non-governmental organizations, can promote the implementation of Internet of Things technology behavior. High-intensity financial support, low-intensity punishment and pressure measures, and moderate direct supervision have the most significant effect on the implementation of Internet of Things technology.

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Section: Evolutionary Game Processmentioning

confidence: 99%

Evolutionary Game Analysis of Non-Governmental Organizations Participating in Garbage Management under the Background of Internet of Things

Cui

et al. 2022

Sustainability

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“…No complex compu-tation is required in this phase, so this phase is implemented by communication. The first stage is ignored in the localization algorithm that does not require ranging [20]. The measurement information between neighboring nodes is obtained from each other by physical measurements or estimated from each other by multihop communication within the network.…”

Section: Related Workmentioning

confidence: 99%

UAV Automation Control System Based on an Intelligent Sensor Network

Jia

Song

2022

Journal of Sensors

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With the widespread use of UAVs, it is gradually difficult for single UAV to meet the needs of increasingly complex scenarios. At the same time, the problems of low autonomy and high dependence on control stations in central UAV cluster networks are gradually highlighted. In this paper, we analyze the theoretical conditions of network topology establishment and network connectivity, design a series of UAV distributed cluster automation control algorithm frameworks, and achieve certain research results, taking the distributed clusters of flight self-organizing networks as the background and using mathematical tools such as algebraic graph theory and random geometry to build a vibration sensor array model based on multiple intelligent sensor management. Based on this, a distributed connectivity maintenance algorithm based on the importance of nodes is designed to realize the “self-healing” of the flight’s self-organizing network. This study also improves the Mavlink flight control communication protocol customization and Zigbee wireless networking mode design to solve the UAV swarm communication link collision problem. Compared with the existing distributed spectrum estimation-based node importance algorithm, the proposed algorithm further analyzes the topological changes caused by the removal of associated edges by failed nodes and the reconstruction of new associated edges between neighboring nodes, so that the theoretical results are closer to the actual topological dynamics of the flight self-organizing network.

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“…In smart cities, the most important issue was the authentication of drones during flight [12]. Thus, the drone with a secure network is important in each zones of the smart city [13]. Most importantly, security with low latency-based authentication mechanism is required for drone-assisted applications [14].…”

Section: Introductionmentioning

confidence: 99%

A Secure Unmanned Aerial Vehicle Service for Medical System to Improve Smart City Facilities

Doraswamy¹,

Krishna²,

Giriprasad³

2022

IJACSA

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The use of drone technology and drones are currently widespread due to their increasing applications. However, there are some specific security-based challenges in the authentication process. In most drone-based applications, there are many authentication approaches, which are subject to handover delay issues with security complexities for an attack. To end these issues, the presented research has focused on developing a novel Optimized deep learning model known as Fruit Fly based UNet Drone Assisted Security (FFUDAS) to remove the malicious attacks. Moreover, the user requests are stored in the cloud, and the stored data are trained to the drones. Hereafter, the drones can deliver medicine to the requestor's location; in that, the malicious attacks were changes the location of drones. Once the attack is identified, then the attack removal process is done. Finally, the new path location to the requested user was identified with the help of fruit fly fitness; then the medicines are delivered to the requested user's location. Furthermore, the designed procedure is executed in an NS2 platform with required nodes. The robustness of the presented model was verified by evaluating the metrics like confidential data rate, execution time, handover delay, pack perception and data delivery rate, and energy consumption. Furthermore, to identify the effectiveness of the presented work, the presented model is compared with other existing schemes. The comparison results show that the presented model has higher throughput, less execution time and handover delay.

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A low-cost physical location discovery scheme for large-scale Internet of Things in smart city through joint use of vehicles and UAVs

Cited by 39 publications

References 25 publications

Evolutionary Game Analysis of Non-Governmental Organizations Participating in Garbage Management under the Background of Internet of Things

Evolutionary Game Analysis of Non-Governmental Organizations Participating in Garbage Management under the Background of Internet of Things

UAV Automation Control System Based on an Intelligent Sensor Network

A Secure Unmanned Aerial Vehicle Service for Medical System to Improve Smart City Facilities

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