| Title | CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting |
|---|---|
| ID_Doc | 42401 |
| Authors | Mathew, SS; El Barachi, M; Kuhail, MA |
| Title | CrowdPower: A Novel Crowdsensing-as-a-Service Platform for Real-Time Incident Reporting |
| Year | 2022 |
| Published | Applied Sciences-Basel, 12, 21 |
| Abstract | Crowdsensing using mobile phones is a novel addition to the Internet of Things applications suite. However, there are many challenges related to crowdsensing, including (1) the ability to manage a large number of mobile users with varying devices' capabilities; (2) recruiting reliable users available in the location of interest at the right time; (3) handling various sensory data collected with different requirements and at different frequencies and scales; (4) brokering the relationship between data collectors and consumers in an efficient and scalable manner; and (5) automatically generating intelligence reports after processing the collected sensory data. No comprehensive end-to-end crowdsensing platform has been proposed despite a few attempts to address these challenges. In this work, we aim at filling this gap by proposing and describing the practical implementation of an end-to-end crowdsensing-as-a-service system dubbed CrowdPower. Our platform offers a standard interface for the management and brokerage of sensory data, enabling the transformation of raw sensory data into valuable smart city intelligence. Our solution includes a model for selecting participants for sensing campaigns based on the reliability and quality of sensors on users' devices, then subsequently analysing the quality of the data provided using a clustering approach to predict user reputation and identify outliers. The platform also has an elaborate administration web portal developed to manage and visualize sensing activities. In addition to the architecture, design, and implementation of the backend platform capabilities, we also explain the creation of CrowdPower's sensing mobile application that enables data collectors and consumers to participate in various sensing activities. |
| https://www.mdpi.com/2076-3417/12/21/11156/pdf?version=1667488690 |
Similar Articles
| ID | Score | Article |
|---|---|---|
67352
|
Capponi, A; Fiandrino, C; Franck, C; Sorger, U; Kliazovich, D; Bouvry, P Assessing Performance of Internet of Things-based Mobile Crowdsensing Systems for Sensing as a Service Applications in Smart Cities(2016) | |
| 43349
|
Regalia, B; McKenzie, G; Gao, S; Janowicz, K Crowdsensing smart ambient environments and services(2016)Transactions In Gis, 20, 3 | |
| 43057
|
Steele, R; Jaimes, LG Crowdsensing sub-populations in a region(2019)Journal Of Ambient Intelligence And Humanized Computing, 10, 4 | |
| 45295
|
Alkhelaiwi, A; Grigoras, D The Origin and Trustworthiness of Data in Smart City Applications(2015) | |
| 44528
|
Foschini, L; Martuscelli, G; Montanari, R; Solimando, M Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events(2021)Journal Of Grid Computing, 19, 3 | |
| 37801
|
Labus, A; Radenkovic, M; Neskovic, S; Popovic, S; Mitrovic, S A Smart City IoT Crowdsensing System Based on Data Streaming Architecture(2022) | |
| 45702
|
Giatsoglou, M; Chatzakou, D; Gkatziaki, V; Vakali, A; Anthopoulos, L CITYPULSE: A Platform Prototype for Smart City Social Data Mining(2016)Journal Of The Knowledge Economy, 7, 2 | |
| 36299
|
Pouryazdan, M; Kantarci, B; Soyata, T; Song, HB Anchor-Assisted and Vote-Based Trustworthiness Assurance in Smart City Crowdsensing(2016) | |
| 39310
|
Yahya, A; Yahya, Y; Misk, N; Hijja, H Human Computation Based Platform for Citizen Services in Smart Cities(2022) | |
| 42858
|
Abu-Elkheir, M; Hassanein, HS; Oteafy, SMA Enhancing Emergency Response Systems through Leveraging Crowdsensing and Heterogeneous Data Analytics(2016) |