Compressive Sensing-Based IoT Applications: A Review
The Internet of Things (IoT) holds great promises to provide an edge cutting technology that enables numerous innovative services related to healthcare, manufacturing, smart cities and various human daily activities. In a typical IoT scenario, a large number of self-powered smart devices collect rea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-10-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2224-2708/7/4/45 |
| _version_ | 1811232815855960064 |
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| author | Hamza Djelouat Abbes Amira Faycal Bensaali |
| author_facet | Hamza Djelouat Abbes Amira Faycal Bensaali |
| author_sort | Hamza Djelouat |
| collection | DOAJ |
| description | The Internet of Things (IoT) holds great promises to provide an edge cutting technology that enables numerous innovative services related to healthcare, manufacturing, smart cities and various human daily activities. In a typical IoT scenario, a large number of self-powered smart devices collect real-world data and communicate with each other and with the cloud through a wireless link in order to exchange information and to provide specific services. However, the high energy consumption associated with the wireless transmission limits the performance of these IoT self-powered devices in terms of computation abilities and battery lifetime. Thus, to optimize data transmission, different approaches have to be explored such as cooperative transmission, multi-hop network architectures and sophisticated compression techniques. For the latter, compressive sensing (CS) is a very attractive paradigm to be incorporated in the design of IoT platforms. CS is a novel signal acquisition and compression theory that exploits the sparsity behavior of most natural signals and IoT architectures to achieve power-efficient, real-time platforms that can grant efficient IoT applications. This paper assesses the extant literature that has aimed to incorporate CS in IoT applications. Moreover, the paper highlights emerging trends and identifies several avenues for future CS-based IoT research. |
| first_indexed | 2024-04-12T11:10:38Z |
| format | Article |
| id | doaj.art-e5907a12037847449df5e737f74e99e8 |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-04-12T11:10:38Z |
| publishDate | 2018-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-e5907a12037847449df5e737f74e99e82022-12-22T03:35:38ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082018-10-01744510.3390/jsan7040045jsan7040045Compressive Sensing-Based IoT Applications: A ReviewHamza Djelouat0Abbes Amira1Faycal Bensaali2College of Engineering, Qatar University, Doha 2713, QatarCollege of Engineering, Qatar University, Doha 2713, QatarCollege of Engineering, Qatar University, Doha 2713, QatarThe Internet of Things (IoT) holds great promises to provide an edge cutting technology that enables numerous innovative services related to healthcare, manufacturing, smart cities and various human daily activities. In a typical IoT scenario, a large number of self-powered smart devices collect real-world data and communicate with each other and with the cloud through a wireless link in order to exchange information and to provide specific services. However, the high energy consumption associated with the wireless transmission limits the performance of these IoT self-powered devices in terms of computation abilities and battery lifetime. Thus, to optimize data transmission, different approaches have to be explored such as cooperative transmission, multi-hop network architectures and sophisticated compression techniques. For the latter, compressive sensing (CS) is a very attractive paradigm to be incorporated in the design of IoT platforms. CS is a novel signal acquisition and compression theory that exploits the sparsity behavior of most natural signals and IoT architectures to achieve power-efficient, real-time platforms that can grant efficient IoT applications. This paper assesses the extant literature that has aimed to incorporate CS in IoT applications. Moreover, the paper highlights emerging trends and identifies several avenues for future CS-based IoT research.http://www.mdpi.com/2224-2708/7/4/45Internet of Things (IoT)compressive sensing (CS)hardware implementationreconstruction algorithms |
| spellingShingle | Hamza Djelouat Abbes Amira Faycal Bensaali Compressive Sensing-Based IoT Applications: A Review Journal of Sensor and Actuator Networks Internet of Things (IoT) compressive sensing (CS) hardware implementation reconstruction algorithms |
| title | Compressive Sensing-Based IoT Applications: A Review |
| title_full | Compressive Sensing-Based IoT Applications: A Review |
| title_fullStr | Compressive Sensing-Based IoT Applications: A Review |
| title_full_unstemmed | Compressive Sensing-Based IoT Applications: A Review |
| title_short | Compressive Sensing-Based IoT Applications: A Review |
| title_sort | compressive sensing based iot applications a review |
| topic | Internet of Things (IoT) compressive sensing (CS) hardware implementation reconstruction algorithms |
| url | http://www.mdpi.com/2224-2708/7/4/45 |
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