Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

Foremski, Paweł; Gorawski, Michał; Grochla, Krzysztof; Połys, Konrad

doi:10.3390/s150922060

Cited by 20 publications

(12 citation statements)

References 45 publications

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“…This is especially relevant in areas with complex topographical characteristics. For this reason, different applications allow to easily measure and share [31] actual service signal strength, generating a crowd-sourced map of actual service availability. Table 3 summarizes a list of crowd-sourced maps to check actual service availability.…”

Section: Service Availability In Sigfox Tm and Gsmmentioning

confidence: 99%

Internet of THings Area Coverage Analyzer (ITHACA) for Complex Topographical Scenarios

et al. 2017

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Abstract:The number of connected devices is increasing worldwide. Not only in contexts like the Smart City, but also in rural areas, to provide advanced features like smart farming or smart logistics. Thus, wireless network technologies to efficiently allocate Internet of Things (IoT) and Machine to Machine (M2M) communications are necessary. Traditional cellular networks like Global System for Mobile communications (GSM) are widely used worldwide for IoT environments. Nevertheless, Low Power Wide Area Networks (LP-WAN) are becoming widespread as infrastructure for present and future IoT and M2M applications. Based also on a subscription service, the LP-WAN technology SIGFOX TM may compete with cellular networks in the M2M and IoT communications market, for instance in those projects where deploying the whole communications infrastructure is too complex or expensive. For decision makers to decide the most suitable technology for each specific application, signal coverage is within the key features. Unfortunately, besides simulated coverage maps, decision-makers do not have real coverage maps for SIGFOX TM , as they can be found for cellular networks. Thereby, we propose Internet of THings Area Coverage Analyzer (ITHACA), a signal analyzer prototype to provide automated signal coverage maps and analytics for LP-WAN. Experiments performed in the Gran Canaria Island, Spain (with both urban and complex topographic rural environments), returned a real SIGFOX TM service availability above 97% and above 11% more coverage with respect to the company-provided simulated maps. We expect that ITHACA may help decision makers to deploy the most suitable technologies for future IoT and M2M projects.

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Section: Service Availability In Sigfox Tm and Gsmmentioning

confidence: 99%

Internet of THings Area Coverage Analyzer (ITHACA) for Complex Topographical Scenarios

et al. 2017

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“…Mobile crowdsensing is a strong paradigm for practically the same problem as participatory sensing [3,4,22,23]. The crowdsensing concepts to location tracking and collection of spatial data have been proposed in [24,25]. It was pointed out that the barriers for engaging people in crowdsensing are the impact on their battery lifetime and phone usage habits in [24].…”

Section: Crowdsensing Frameworkmentioning

confidence: 99%

“…The crowdsensing concepts to location tracking and collection of spatial data have been proposed in [24,25]. It was pointed out that the barriers for engaging people in crowdsensing are the impact on their battery lifetime and phone usage habits in [24]. To address these requirements, they proposed an energy-efficient application for measuring the location and signal strength data.…”

Section: Crowdsensing Frameworkmentioning

confidence: 99%

A Web GIS Framework for Participatory Sensing Service: An Open Source-Based Implementation

et al. 2017

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Participatory sensing is the process in which individuals or communities collect and analyze systematic data using mobile phones and cloud services. To efficiently develop participatory sensing services, some server-side technologies have been proposed. Although they provide a good platform for participatory sensing, they are not optimized for spatial data management and processing. For the purpose of spatial data collection and management, many web GIS approaches have been studied. However, they still have not focused on the optimal framework for participatory sensing services. This paper presents a web GIS framework for participatory sensing service (FPSS). The proposed FPSS enables an integrated deployment of spatial data capture, storage, and data management functions. In various types of participatory sensing experiments, users can collect and manage spatial data in a unified manner. This feature is realized by the optimized system architecture and use case based on the general requirements for participatory sensing. We developed an open source GIS-based implementation of the proposed framework, which can overcome financial difficulties that are one of the major problems of deploying sensing experiments. We confirmed with the prototype that participatory sensing experiments can be performed efficiently with the proposed FPSS.

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“…Such service may be one that is offered using the aggregated crowdsensed data as demonstrated in [39][40][41]. In other cases, a service that provides utility to a broad gamut of society is used as incentive, not one that necessarily derives its value from the crowdsensed data.…”

Section: Service Incentivesmentioning

confidence: 99%

Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework

Ogie

2016

Hum. Cent. Comput. Inf. Sci.

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Mobile crowdsensing is a burgeoning concept that allows smart cities to leverage the sensing power and ubiquitous nature of mobile devices in order to capture and map phenomena of common interest. At the core of any successful mobile crowdsensing application is active user participation, without which the system is of no value in sensing the phenomenon of interest. A major challenge militating against widespread use and adoption of mobile crowdsensing applications is the issue of how to identify the most appropriate incentive mechanism for adequately and efficiently motivating participants. This paper reviews literature on incentive mechanisms for mobile crowdsensing and proposes the concept of SPECTRUM as a guide for inferring the most appropriate type of incentive suited to any given crowdsensing task. Furthermore, the paper highlights research challenges and areas where additional studies related to the different factors outlined in the concept of SPECTRUM are needed to improve citizen participation in mobile crowdsensing. It is envisaged that the broad range of factors covered in SPECTRUM will enable smart cities to efficiently engage citizens in large-scale crowdsensing initiatives. More importantly, the paper is expected to trigger empirical investigations into how various factors as outlined in SPECTRUM can influence the type of incentive mechanism that is considered most appropriate for any given mobile crowdsensing initiative.

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Energy-Efficient Crowdsensing of Human Mobility and Signal Levels in Cellular Networks

Cited by 20 publications

References 45 publications

Internet of THings Area Coverage Analyzer (ITHACA) for Complex Topographical Scenarios

Internet of THings Area Coverage Analyzer (ITHACA) for Complex Topographical Scenarios

A Web GIS Framework for Participatory Sensing Service: An Open Source-Based Implementation

Adopting incentive mechanisms for large-scale participation in mobile crowdsensing: from literature review to a conceptual framework

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