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      A Blockchain-Based Spatial Crowdsourcing System for Spatial Information Collection Using a Reward Distribution

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          Abstract

          Due to the increasing relevance of spatial information in different aspects of location-based services, various methods are used to collect this information. The use of crowdsourcing due to plurality and distribution is a remarkable strategy for collecting information, especially spatial information. Crowdsourcing can have a substantial effect on increasing the accuracy of data. However, many centralized crowdsourcing systems lack security and transparency due to a trusted party’s existence. With the emergence of blockchain technology, there has been an increase in security, transparency, and traceability in spatial crowdsourcing systems. In this paper, we propose a blockchain-based spatial crowdsourcing system in which workers confirm or reject the accuracy of tasks. Tasks are reports submitted by requesters to the system; a report comprises type and location. To our best knowledge, the proposed system is the first system that all participants receive rewards. This system considers spatial and non-spatial reward factors to encourage users’ participation in collecting accurate spatial information. Privacy preservation and security of spatial information are considered in the system. We also evaluated the system efficiency. According to the experiment results, using the proposed system, information accuracy increased by 40%, and the minimum time for reviewing reports by facilities reduced by 30%. Moreover, we compared the proposed system with the current centralized and distributed crowdsourcing systems. This comparison shows that, although our proposed system omits the user’s history to preserve privacy, it considers a consensus-based approach to guarantee submitted reports’ accuracy. The proposed system also has a reward mechanism to encourage more participation.

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          Can Blockchain Strengthen the Internet of Things?

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                29 July 2021
                August 2021
                : 21
                : 15
                : 5146
                Affiliations
                [1 ]Department of GIS, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran 19967-15433, Iran; mrmalek@ 123456kntu.ac.ir
                [2 ]Department of Geomatics Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada; steve.liang@ 123456ucalgary.ca
                Author notes
                Author information
                https://orcid.org/0000-0001-8226-3354
                https://orcid.org/0000-0002-0893-8197
                https://orcid.org/0000-0003-1480-6382
                Article
                sensors-21-05146
                10.3390/s21155146
                8347879
                34372384
                2108be0d-aaac-4bd7-8f12-453d8b3c9b3f
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 13 July 2021
                : 26 July 2021
                Categories
                Article

                Biomedical engineering
                blockchain,location-based services,crowdsourcing,reward algorithm
                Biomedical engineering
                blockchain, location-based services, crowdsourcing, reward algorithm

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