Using IoT devices for fast data processing

A specially designed microcontroller with event-driven sensor data processing unit (EPU) is proposed to provide energy-efficient sensor data acquisition for Internet of Things (IoT) devices in rare-event human activity sensing applications. Rare-event sensing applications using a remotely installed IoT sensor device have a property of very long event-to-event distance, so that the inaccurate sensor data processing in a certain range of accuracy error is enough to extract appropriate events from the collected sensing data. The proposed signal-to-event converter (S2E) as a preprocessor of the conventional sensor interface extracts a set of atomic events with the specific features of interest and performs an early evaluation for the featured points of the incoming sensor signal. The conventional sensor data processing such as DSPs or software-driven algorithm to classify the meaningful event from the collected sensor data could be accomplished by the proposed event processing unit (EPU). The proposed microcontroller architecture enables an energy efficient signal processing for rare-event sensing applications. The implemented system-on-chip (SoC) including the proposed building blocks is fabricated with additional 7500 NAND gates and 1-KB SRAM tracer in 0.18 um CMOS process, consuming only 20% compared to the conventional sensor data processing method for human hand-gesture detection.

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Microservice-Oriented Platform for Internet of Big Data Analytics: A Proof of Concept

Sensors ◽

10.3390/s19051134 ◽

2019 ◽

Vol 19 (5) ◽

pp. 1134 ◽

Cited By ~ 5

Author(s):

Zheng Li ◽

Diego Seco ◽

Alexis Sánchez Rodríguez

Keyword(s):

Big Data ◽

Resource Management ◽

Data Processing ◽

Data Analytics ◽

Big Data Analytics ◽

Proof Of Concept ◽

Tight Coupling ◽

Specific Data ◽

Numerous Data ◽

Iot Devices

The ubiquitous Internet of Things (IoT) devices nowadays are generating various and numerous data from everywhere at any time. Since it is not always necessary to centralize and analyze IoT data cumulatively (e.g., the Monte Carlo analytics and Convergence analytics demonstrated in this article), the traditional implementations of big data analytics (BDA) will suffer from unnecessary and expensive data transmissions as a result of the tight coupling between computing resource management and data processing logics. Inspired by software-defined infrastructure (SDI), we propose the “microservice-oriented platform” to break the environmental monolith and further decouple data processing logics from their underlying resource management in order to facilitate BDA implementations in the IoT environment (which we name “IoBDA”). Given predesigned standard microservices with respect to specific data processing logics, the proposed platform is expected to largely reduce the complexity in and relieve inexperienced practices of IoBDA implementations. The potential contributions to the relevant communities include (1) new theories of a microservice-oriented platform on top of SDI and (2) a functional microservice-oriented platform for IoBDA with a group of predesigned microservices.

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ProceThings: Data Processing Platform with In-situ IoT Devices for Smart Community Services

Adjunct Proceedings of the 2021 International Conference on Distributed Computing and Networking ◽

10.1145/3427477.3429275 ◽

2020 ◽

Author(s):

Yugo Nakamura ◽

Jose Paolo Talusan ◽

Teruhiro Mizumoto ◽

Hirohiko Suwa ◽

Yutaka Arakawa ◽

...

Keyword(s):

Data Processing ◽

Community Services ◽

Iot Devices ◽

Smart Community ◽

Processing Platform

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Reliable Vehicle Data Storage Using Blockchain and IPFS

Electronics ◽

10.3390/electronics10101130 ◽

2021 ◽

Vol 10 (10) ◽

pp. 1130

Author(s):

Hyoeun Ye ◽

Sejin Park

Keyword(s):

Data Processing ◽

Data Storage ◽

Processing Speed ◽

Experimental Results ◽

Superior Performance ◽

Distributed Application ◽

Vehicle Data ◽

Iot Devices

As the importance of vehicle data increases, it has become very important to safely store them. However, because onboard diagnostics scanners generally used to store vehicle data are IoT devices, security and capacity issues exist to store data safely and efficiently. To address this, we propose a system that stores vehicle data safely and efficiently using blockchain and IPFS. Users can access the system through DApp, an Ethereum-distributed application, and manage their vehicle data. Various experiments have been conducted to demonstrate the superior performance of this system, and the experimental results show its advantages in terms of data-processing speed and cost.

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Fine-Grained Data Processing Framework for Heterogeneous IoT Devices in Sub-aquatic Edge Computing Environment

Wireless Personal Communications ◽

10.1007/s11277-020-07803-3 ◽

2020 ◽

Author(s):

Jahwan Koo ◽

Nawab Muhammad Faseeh Qureshi

Keyword(s):

Data Processing ◽

Edge Computing ◽

Computing Environment ◽

Fine Grained ◽

Iot Devices ◽

Processing Framework

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BSCL: Blockchain-Oriented SDN Controlled Cloud Based Li-Fi Communication Architecture for Smart City Network

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i4.38.27602 ◽

2018 ◽

Vol 7 (4.38) ◽

pp. 888

Author(s):

Fazeel Ahmed Khan ◽

Adamu Abubakar ◽

Marwan Mahmoud ◽

Mahmoud Ahmad Al-Khasawneh ◽

Ala Abdulsalam Alarood ◽

...

Keyword(s):

Data Processing ◽

Smart City ◽

High Speed ◽

The Internet ◽

Cloud Infrastructure ◽

Network Infrastructure ◽

Communication Architecture ◽

Proposed Model ◽

High Speed Data ◽

Iot Devices

The Internet of Things (IoT) smart city initiative has transformed technology spectrum into its new era of development. The increasing amount of data generated by millions of IoT devices and the rapid flow of data across distributed IoT devices are transmitting to remotely located cloud infrastructure over the Internet. Unfortunately, these large amounts of data and its flow based on the traditional energy-intensive network infrastructure is neither efficient nor substantially scalable. It is essential to design a comprehensive network infrastructure to handle large amount of high-speed data-processing in an IoT spectrum. Apparently, Blockchain and Software-Defined Networking (SDN) approaches can leveraged the scalability of the environment for IoT spectrum. In addition, the emergence of distributed cloud technology and Li-Fi spectrum can transform the capability of data-processing for IoT devices. The challenge lies in efficiently blend the integration of Li-Fi, Blockchain, SDN and Cloud technologies for IoT environment. To address this challenge, we design a multiaccess communication modulation model for efficient optimization of distributed network with an SDN based controller and integration of robust cloud infrastructure for high-speed data-processing. The proposed model is based on Li-Fi communication architecture which significantly reduced in the utilization of energy for managing large-scale infrastructure. We performed simulation and analysis across multiple dimensions to evaluate the performance and effectiveness of our proposed model. The evaluated output shows that our model significantly improved the overall performance and efficiency of the communication infrastructure as compared with other ultra-modern models.

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