STERILIZER CHAMBER DESIGN WITH TELEGRAM-BASED INTERNET OF THINGS (IoT) APPLICATIONS

This article presents a simple wideband rectangular antenna in foldable and non-foldable (printed circuit board (PCB)) structures for Internet of Things (IoT) applications. Both are simple structures with two similar rectangular metal planes which cover multiple frequency bands such as GPS, WCDMA/LTE, and 2.4 GHz industrial, scientific, and medical (ISM) bands. This wideband antenna is suitable to integrate into the short- and long-range wireless applications such as the short-range 2.4 GHz ISM band and standard cellular bands. This lowers the overall size of the product as well as the cost in the applications. In this article, the configuration and operation principle are presented as well as its trade-offs on the design parameters. Simulated and experimental results of foldable and non-foldable (PCB) structures show that the antenna is suited for IoT applications.

Download Full-text

Machine Learning and LPWAN Based Internet of Things Applications in Healthcare Sector during COVID-19 Pandemic

Electronics ◽

10.3390/electronics10141615 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1615

Author(s):

Zeeshan Ali Khan ◽

Ubaid Abbasi ◽

Sung Won Kim

Keyword(s):

Machine Learning ◽

Internet Of Things ◽

Healthcare Services ◽

Healthcare Sector ◽

K Nearest Neighbors ◽

Iot Applications ◽

Processing Resources ◽

Multiple Services ◽

Applications Of Machine Learning

Low power wide area networks (LPWAN) are comprised of small devices having restricted processing resources and limited energy budget. These devices are connected with each other using communication protocols. Considering their available resources, these devices can be used in a number of different Internet of Things (IoT) applications. Another interesting paradigm is machine learning, which can also be integrated with LPWAN technology to embed intelligence into these IoT applications. These machine learning-based applications combine intelligence with LPWAN and prove to be a useful tool. One such IoT application is in the medical field, where they can be used to provide multiple services. In the scenario of the COVID-19 pandemic, the importance of LPWAN-based medical services has gained particular attention. This article describes various COVID-19-related healthcare services, using the the applications of machine learning and LPWAN in improving the medical domain during the current COVID-19 pandemic. We validate our idea with the help of a case study that describes a way to reduce the spread of any pandemic using LPWAN technology and machine learning. The case study compares k-Nearest Neighbors (KNN) and trust-based algorithms for mitigating the flow of virus spread. The simulation results show the effectiveness of KNN for curtailing the COVID-19 spread.

Download Full-text

Self-Synchronization in Duty-Cycled Internet of Things (IoT) Applications

IEEE Internet of Things Journal ◽

10.1109/jiot.2017.2757138 ◽

2017 ◽

Vol 4 (6) ◽

pp. 2058-2069 ◽

Cited By ~ 10

Author(s):

Poonam Yadav ◽

Julie A. McCann ◽

Tiago Pereira

Keyword(s):

Internet Of Things ◽

Iot Applications

Download Full-text

Key IOT Technology and Application Research

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.543-547.3411 ◽

2014 ◽

Vol 543-547 ◽

pp. 3411-3414

Author(s):

Xu Bing

Keyword(s):

Wireless Sensor Network ◽

Internet Of Things ◽

Intelligent Transportation System ◽

Rapid Development ◽

Intelligent Transportation ◽

Wireless Sensor ◽

Medical Monitoring ◽

Application Research ◽

Iot Applications ◽

Architectural Model

Key core technologies of IOT (internet of things) have to be addressed to achieve rapid development. This paper focused on studying RFID, wireless sensor network (WSN) and TCCP which were integrated to address the IOT application problems. Meanwhile, an IOT architectural model was established and the IOT applications in real-time medical monitoring, intelligent transportation system (ITS), intelligent appliances and intelligent agriculture were introduced.

Download Full-text