From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs

Erdelj, Milan; Uk, Borey; Konam, David; Natalizio, Enrico

doi:10.3390/s18113814

Cited by 22 publications

(9 citation statements)

References 14 publications

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“…It is thus natural to look at environmental monitoring as a big and complex service that can be supported by such emerging architectures. For instance, in [443], it was shown that a combination of smartphones, sensors, and UAVs can effectively overcome the limitations of an unstable communication environment in the presence of a natural disaster. However, several other aspects besides communication should be taken into account to treat the topic in its entirety.…”

Section: Combining Wsn/uav/crowdsensing and Advanced Signal Processingmentioning

confidence: 99%

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Fascista

2022

Sensors

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Fighting Earth’s degradation and safeguarding the environment are subjects of topical interest and sources of hot debate in today’s society. According to the United Nations, there is a compelling need to take immediate actions worldwide and to implement large-scale monitoring policies aimed at counteracting the unprecedented levels of air, land, and water pollution. This requires going beyond the legacy technologies currently employed by government authorities and adopting more advanced systems that guarantee a continuous and pervasive monitoring of the environment in all its different aspects. In this paper, we take the research on integrated and large-scale environmental monitoring a step further by providing a comprehensive review that covers transversally all the main applications of wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs), and crowdsensing monitoring technologies. By outlining the available solutions and current limitations, we identify in the cooperation among terrestrial (WSN/crowdsensing) and aerial (UAVs) sensing, coupled with the adoption of advanced signal processing techniques, the major pillars at the basis of future integrated (air, land, and water) and large-scale environmental monitoring systems. This review not only consolidates the progresses achieved in the field of environmental monitoring, but also sheds new lights on potential future research directions and synergies among different research areas.

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Section: Combining Wsn/uav/crowdsensing and Advanced Signal Processingmentioning

confidence: 99%

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Fascista

2022

Sensors

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“…One step further, Erdelj et al [30] classify different types of disasters considering geophysical, climate-induced and meteorological issues, and propose suitable WSN and UAV-based network architectures for each category. Eventually, an IoT-UAV ecosystem is devised by Erdelj et al [31], in order to provide real-time data and multimedia communications in unstable communication environments by means of a multi-UAV system, which also offers on-demand usage of available sensors, smartphones and UAV infrastructure.…”

Section: B Uav-based Networkmentioning

confidence: 99%

Optimal Energy Management of UAV-Based Cellular Networks Powered by Solar Panels and Batteries: Formulation and Solutions

2019

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We focus on the problem of managing the energy consumption of a cellular network tailored to cover rural and low-income areas. The considered architecture exploits Unmanned Aerial Vehicles (UAVs) to ensure wireless coverage, as well as Solar Panels (SPs) and batteries installed in a set of ground sites, which provides the energy required to recharge the UAVs. We then target the maximization of the energy stored in the UAVs and in the ground sites, by ensuring the coverage of the territory through the scheduling of the UAV missions over space and time. After providing the problem formulation, we face its complexity by proposing a decomposition-based approach and by designing a brand-new genetic algorithm. The results, obtained over a set of representative case studies, reveal that there exists a trade-off between the UAVs battery level, the ground sites battery level, and the level of coverage. In addition, both the decomposed version and the genetic algorithm perform sufficiently close to the integrated model, with a strong improvement in the computation times.INDEX TERMS Energy management, mixed integer linear programming, renewable energy sources, Unmanned Aerial Vehicles, UAV mission scheduling, cellular networks.

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“…UAVs are classified as aerial robots that are used for several tasks in different application domains. They can be used for Aerial Photography [ 4 ], or as Pesticide sprinkler [ 5 ], Ambulance UAVs [ 6 ], for search and rescue operations [ 7 ], disaster management [ 8 , 9 , 10 ], filming Sport Event [ 11 ], infrastructure inspection [ 12 ], air pollution monitoring [ 13 ], traffic policing and emergency response [ 14 ], etc. In the mentioned applications, UAVs could coordinate to establish an effective coverage path planning (CPP).…”

Section: Introductionmentioning

confidence: 99%

PPS: Energy-Aware Grid-Based Coverage Path Planning for UAVs Using Area Partitioning in the Presence of NFZs

Ghaddar

Merei

Natalizio

2020

Sensors

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Area monitoring and surveillance are some of the main applications for Unmanned Aerial Vehicle (UAV) networks. The scientific problem that arises from this application concerns the way the area must be covered to fulfill the mission requirements. One of the main challenges is to determine the paths for the UAVs that optimize the usage of resources while minimizing the mission time. Different approaches rely on area partitioning strategies. Depending on the size and complexity of the area to monitor, it is possible to decompose it exactly or approximately. This paper proposes a partitioning method called Parallel Partitioning along a Side (PPS). In the proposed method, grid-mapping and grid-subdivision of the area, as well as area partitioning are performed to plan the UAVs path. An extra challenge, also tackled in this work, is the presence of non-flying zones (NFZs). These zones are areas that UAVs must not cover or pass over it. The proposal is extensively evaluated, in comparison with existing approaches, to show that it enables UAVs to plan paths with minimum energy consumption, number of turns and completion time while at the same time increases the quality of coverage.

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From the Eye of the Storm: An IoT Ecosystem Made of Sensors, Smartphones and UAVs

Cited by 22 publications

References 14 publications

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Toward Integrated Large-Scale Environmental Monitoring Using WSN/UAV/Crowdsensing: A Review of Applications, Signal Processing, and Future Perspectives

Optimal Energy Management of UAV-Based Cellular Networks Powered by Solar Panels and Batteries: Formulation and Solutions

PPS: Energy-Aware Grid-Based Coverage Path Planning for UAVs Using Area Partitioning in the Presence of NFZs

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