UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Hu, Zhiwen; Bai, Zixuan; Yang, Yuzhe; Zheng, Zijie; Bian, Kaigui; Song, Lingyang

doi:10.1109/mnet.2019.1800214

Cited by 96 publications

(46 citation statements)

References 15 publications

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“…In line with this, there are numerous studies relating to the notion of a smart campus [49], focusing on different specific sectors, such as the management of the growing number of devices [50]; IoT architectures [51][52][53]; energy management and air quality [54,55]; flexible architectures [56][57][58][59]; sensor networks [60]; big data [53]; semantic interoperability [61]; or knowledge management [62]. Research has also been conducted on global smart university solutions, though these are implemented for specific campuses, as in [63,64].…”

Section: Background and Motivationmentioning

confidence: 99%

Modelling and Implementing Smart Universities: An IT Conceptual Framework

2021

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The smart city concept has been gaining momentum in the scientific community because of its potentially huge impact on citizens’ quality of life. However, expectations have not yet been met in practice. This is firstly due to the sheer breadth of such projects and secondly to the lack of methodologies available to guide the development of flexible and sustainable platforms over time. In this work, we propose to address these issues by using a university campus as a less complex mock-up version of a city. Despite differences between them, we find services that are common to both, and a medium-sized city’s population is comparable to that of a university community. We propose an IT conceptual framework to model and implement smart university projects, which supports the design of a platform that is both in line with the strategic plans of universities and is flexible, sustainable, stable, and sufficiently modular to support the addition of different value-added services over the years. Our framework is based on a service provision model materialised in an IT architecture and managed following a methodology to integrate IT components that ensure the insertion of new, smart initiatives of value to the community, aligned with the university’s needs, via a value-added service planning process. The results are presented in the University of Alicante case study and the SmartUA project.

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Section: Background and Motivationmentioning

confidence: 99%

Modelling and Implementing Smart Universities: An IT Conceptual Framework

2021

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“…In [25], a smart city architecture is proposed where UAVs form a 5G hierarchical IoT network in the sky, linking to a number of BSs on the ground. An architecture is presented in [26] considering UAV-aided IoT for air quality sensing in smart cities. These studies mainly focused on network architecture and UAV trajectory optimization.…”

Section: Related Workmentioning

confidence: 99%

Priority-Aware Fast MAC Protocol for UAV-Assisted Industrial IoT Systems

Khisa

Moh

2021

IEEE Access

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Many hazardous industrial incidents can occur due to the inadequate and inefficient monitoring of the offshore plants. Manual inspections of the offshore plants on a regular basis is not only time consuming but also dangerous regarding to human safety. For considering the safety measurement and alleviating the burden of the manual inspection, unmanned aerial vehicles (UAVs) can be effectively utilized to collect data from the remote industrial environment. In an industrial scenario, less delay is required for emergency packets and high throughput is needed for monitoring packets. This paper proposes a priority-aware fast MAC (PF-MAC) protocol for UAV-assisted industrial Internet-of-things (IIoT) systems, ensuring fast and robust data delivery. At first, the IoT devices under the UAV communication range transmit a reservation frame to the UAV to catch transmission opportunities using CSMA/CA. The devices utilize static traffic priority and a novel adaptive backoff mechanism during CSMA/CA. After receiving the reservation frames from the IoT devices, the UAV calculates the dynamic device priority based on their static traffic priority, communication duration, sampling frequency, and remaining energy. Then, time slot is assigned by the UAV to each device for data transmission. To ensure fairness, if a device fails in contention during the CSMA/CA period, the static traffic priority is raised in the next retransmission. There is no prior work in the literature that considers both the traffic priority and the device priority to ensure Quality of Service in IIoT and related systems. According to our performance study, the proposed PF-MAC outperforms the conventional protocols in terms of delay and throughput.INDEX TERMS Internet of Things, unmanned aerial vehicle, medium access control, traffic priority, device priority, delay, quality of service.Shreya Khisa received the B.S. degree in computer science and engineering from University of Chittagong, Bangladesh in 2017. She is currently pursuing the M.S. degree with the Mobile Computing Laboratory, Chosun University, South Korea. Her current research interests include wireless sensor networks, Internet of things, and unmanned aerial vehicle networks with a focus on network architectures and protocols.

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“…The system architecture consists of a sensor layer for data collection, a transmission layer to enable twoway communications, a processing layer for data analysis and manipulation, and a presentation layer to provide a graphical interface to users. System disadvantages: at the sensor layer, sensor and data download are not expected continuously due to limited battery capacity [34].…”

Section: Literature Reviewmentioning

confidence: 99%

A Survey on Smart Monitoring System of Environment Based on IoT

AlSheikh¹,

Hagem²

2021

(AREJ)

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This paper introduces different topics about Air pollution monitoring based on IoT (internet of things). It describes different methods used for monitoring and measuring Air pollution using different techniques. Some papers discussed Air pollution monitoring using (Arduino uno, Raspberry or ESP8266, PIC microcontroller). All would be presented to improve air monitoring efficiently and to clarify the tools used in each technique giving the differences between one technique and another. Reducing air pollution is necessary for the future, and cities around the world are using technology and smart city initiatives to take on the problem because it is considered as the major environmental risk factor for human health. Air pollution causes heart disease, stroke, chronic obstructive pulmonary disease, lung cancer and acute lower respiratory disease. Therefore, it is important to reduce traffic and output from factories to decrease pollution

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UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

Cited by 96 publications

References 15 publications

Modelling and Implementing Smart Universities: An IT Conceptual Framework

Modelling and Implementing Smart Universities: An IT Conceptual Framework

Priority-Aware Fast MAC Protocol for UAV-Assisted Industrial IoT Systems

A Survey on Smart Monitoring System of Environment Based on IoT

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