Processing Large Volumes of Data in Sensors and Sensing Technologies
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".
Deadline for manuscript submissions: closed (30 July 2023) | Viewed by 449
Special Issue Editors
Interests: model order reduction; thermal analysis; VLSI design; integrated circuits; electronic design automation; embedded systems; numerical analysis; circuit simulation
Special Issues, Collections and Topics in MDPI journals
Interests: parallel computing’ near-data processing; in-memory computing; dataflow architectures; IoT networks; memory hierarchy design; application-specific integrated circuits
Special Issues, Collections and Topics in MDPI journals
Interests: computer architecture; general-purpose processors; systems on a chip; multi-chip processors; multi-core architectures; edge architectures; accelerators; big-data architectures
Interests: average and maximum power estimation and minimization; hardware security; low power design and architecture; reliability and verification of VLSI circuits; CAD system design; telecom and signal processing circuit optimization; wireless sensor networks and applications; sensor signal processing; safety and security; optimization theory and applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The explosion of data in the last decade imposes a series of challenges in the electronics and data processing domains. Emerging technologies such as 3D sensing, wearable devices, nanosensors, remote sensing and IoT ecosystems have disrupted the industry and have exponentially increased the volume of data being generated. As a result, well-established paradigms like monolithic computing, centralized data collection, structured data processing and general-purpose systems fall short on keeping up with the ever-increasing data volume. Such approaches cannot efficiently handle the storage, processing and energy requirements of memory intensive applications. As a result, emerging technologies that seek to tackle these challenges are gaining traction. Such technologies diverge from the standard data processing and computational approaches, and they leverage either application-specific systems or unique data management schemes to boost application performance and to minimize power consumption. These include but are not limited to: Distributed data processing, in-memory computing, non-volatile memories, near-sensor computing, application-specific designs, low-power electronics for IoT networks, decentralized technologies, efficient deep learning in sensor systems, signal processing optimizations for remote sensing, unstructured data schemas, data fusion, optoelectronic and photonic systems and localization and object tracking algorithms. This Special Issues is addressed to all types of computing, data processing and sensing technologies capable of managing large volumes of data.
Dr. George Floros
Dr. Athanasios Tziouvaras
Dr. Georgios Dimitriou
Prof. Dr. George Stamoulis
Guest Editors
Manuscript Submission Information
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Keywords
- data processing in IoT
- in-memory computing
- AI for image and video applications
- decentralized data technologies
- optoelectronic and photonic sensor systems
- near-sensor processing
- parallel and distributed computing
- low power electronic designs
- localization and object tracking
- machine learning for sensor networks
