Cooperative data muling from ground sensors to base stations using UAVs

Tuyishimire, Emmanuel; Bagula, Antoine; Rekhis, Slim; Boudriga, Noureddine

doi:10.1109/iscc.2017.8024501

Cited by 42 publications

(22 citation statements)

References 8 publications

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“…On the other hand, additional factors associated with pedestrians movements should be included in the presented SFM, such as pedestrian's psychology and pedestrian density. (2) Following the connected UAV approach [53,54], the experiment at one traffic intersection will be extended to monitoring and simulating pedestrian movements at a set of intersections, simultaneously using connected UAVs [55] and cloud services [43].…”

Section: Discussionmentioning

confidence: 99%

Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

Zhu

Chen

et al. 2019

Remote Sensing

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For a city to be livable and walkable is the ultimate goal of future cities. However, conflicts among pedestrians, vehicles, and cyclists at traffic intersections are becoming severe in high-density urban transportation areas, especially in China. Correspondingly, the transit time at intersections is becoming prolonged, and pedestrian safety is becoming endangered. Simulating pedestrian movements at complex traffic intersections is necessary to optimize the traffic organization. We propose an unmanned aerial vehicle (UAV)-based method for tracking and simulating pedestrian movements at intersections. Specifically, high-resolution videos acquired by a UAV are used to recognize and position moving targets, including pedestrians, cyclists, and vehicles, using the convolutional neural network. An improved social force-based motion model is proposed, considering the conflicts among pedestrians, cyclists, and vehicles. In addition, maximum likelihood estimation is performed to calibrate an improved social force model. UAV videos of intersections in Shenzhen are analyzed to demonstrate the performance of the presented approach. The results demonstrate that the proposed social force-based motion model can effectively simulate the movement of pedestrians and cyclists at road intersections. The presented approach provides an alternative method to track and simulate pedestrian movements, thus benefitting the organization of pedestrian flow and traffic signals controlling the intersections.

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Section: Discussionmentioning

confidence: 99%

Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

Zhu

Chen

et al. 2019

Remote Sensing

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“…In the traffic environment, UAV's real-time monitoring technology can be used to help rescue when traffic accidents happen. The speed of the rescue personnel arriving at the accident site is directly related to the work efficiency of the rescue personnel and then affects the life safety of the accident personnel [30]. When the nearest rescue team terminal is too far from the accident site, it may take too long for the rescue team to reach the scene.…”

Section: ) Uav's Real-time Monitoring Technologymentioning

confidence: 99%

Overview of Vehicle Optical Wireless Communications

et al. 2020

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Effective information transmission between vehicles has become one of the solutions to improve road safety. Based on the huge advantages of optical wireless data transmission technology, this paper summarizes the research status of unmanned vehicles in optical wireless communication (OWC). The article not only studies the actual progress of building optical links through an unmanned vehicle, connecting air communication, ground communication, and underwater communication into a unified wireless network, and realizing the fast, stable, large-capacity data transmission system. The technical challenges of unmanned vehicle OWC are also discussed and its future development has prospected. INDEX TERMS optical wireless communication, communication and networking, unmanned aerial vehicles, ground operated vehicles, autonomous underwater vehicle

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“…Of course, in this article, we solve the mathematical formula of the problem as MILP optimization model. Some applications that are real-time, soft, or hard need to process or send data at a specific deadline time (5). In this research, we take into account energy in addition to deadline time, to make routing such that applications with this particular constraint to be included.…”

Section: Figure 1the Relationship Between Uavs and Iot Devicesmentioning

confidence: 99%

Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications

Journal¹

2018

Baghdad Sci.J

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The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming model (MILP) and then we used a heuristic to solve the time complexity problem. The results obtained in the simulation results indicate the optimal performance of the proposed scheme in terms of energy consumption and the number of used UAVs.

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Cooperative data muling from ground sensors to base stations using UAVs

Cited by 42 publications

References 8 publications

Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

Tracking and Simulating Pedestrian Movements at Intersections Using Unmanned Aerial Vehicles

Overview of Vehicle Optical Wireless Communications

Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications

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