Visible to the public Biblio

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2022-01-31
Wang, Zhihui, Sun, Peng, Luo, Nana, Guo, Benzhen.  2021.  A Three-Party Mutual Authentication Protocol for Wearable IOT Health Monitoring System. 2021 IEEE International Conference on Smart Internet of Things (SmartIoT). :344—347.
Recently, the frequent security incidents of the Internet of things make the wearable IOT health monitoring systems (WIHMS) face serious security threats. Aiming at the security requirements of WIHMS identity authentication, Q. Jiang proposed a lightweight device mutual identity authentication solution in 2019. The scheme has good security performance. However, we find that in Jiang’s scheme, in the authentication phase, the server CS needs at least 3 queries and 1 update of the database operation, which affects the overall performance of the system. For this reason, we propose a new device mutual authentication and key agreement protocol. In our protocol, the authentication server only needs to query the server database twice.
2021-05-20
Mheisn, Alaa, Shurman, Mohammad, Al-Ma’aytah, Abdallah.  2020.  WSNB: Wearable Sensors with Neural Networks Located in a Base Station for IoT Environment. 2020 7th International Conference on Internet of Things: Systems, Management and Security (IOTSMS). :1—4.
The Internet of Things (IoT) is a system paradigm that recently introduced, which includes different smart devices and applications, especially, in smart cities, e.g.; manufacturing, homes, and offices. To improve their awareness capabilities, it is attractive to add more sensors to their framework. In this paper, we propose adding a new sensor as a wearable sensor connected wirelessly with a neural network located on the base station (WSNB). WSNB enables the added sensor to refine their labels through active learning. The new sensors achieve an average accuracy of 93.81%, which is 4.5% higher than the existing method, removing human support and increasing the life cycle for the sensors by using neural network approach in the base station.
2020-12-15
Eamsa-ard, T., Seesaard, T., Kerdcharoen, T..  2018.  Wearable Sensor of Humanoid Robot-Based Textile Chemical Sensors for Odor Detection and Tracking. 2018 International Conference on Engineering, Applied Sciences, and Technology (ICEAST). :1—4.

This paper revealed the development and implementation of the wearable sensors based on transient responses of textile chemical sensors for odorant detection system as wearable sensor of humanoid robot. The textile chemical sensors consist of nine polymer/CNTs nano-composite gas sensors which can be divided into three different prototypes of the wearable humanoid robot; (i) human axillary odor monitoring, (ii) human foot odor tracking, and (iii) wearable personal gas leakage detection. These prototypes can be integrated into high-performance wearable wellness platform such as smart clothes, smart shoes and wearable pocket toxic-gas detector. While operating mode has been designed to use ZigBee wireless communication technology for data acquisition and monitoring system. Wearable humanoid robot offers several platforms that can be applied to investigate the role of individual scent produced by different parts of the human body such as axillary odor and foot odor, which have potential health effects from abnormal or offensive body odor. Moreover, wearable personal safety and security component in robot is also effective for detecting NH3 leakage in environment. Preliminary results with nine textile chemical sensors for odor biomarker and NH3 detection demonstrates the feasibility of using the wearable humanoid robot to distinguish unpleasant odor released when you're physically active. It also showed an excellent performance to detect a hazardous gas like ammonia (NH3) with sensitivity as low as 5 ppm.