Internet of Things

The Internet of Things (IoT) is gradually changing the way teaching and learning take place in on-campus programs. In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. However, reducing response latency and executing face analysis services effectively in real-time is still challenging. For this reason, this paper proposed a pedagogical model of face recognition for IoT devices based on edge computing (TFREC)...

The rapid growth of the Internet of Things and wearable sensors has led to advancements in monitoring technology in the field of health. One such advancement is the development of wearable respiratory sensors, which offer a new approach to real-time respiratory monitoring compared to traditional methods. However, the energy consumption of these sensors raises concerns about environmental pollution. To address the issue, this study proposes the use of a triboelectric nanogenerator (TENG) as a sustainable energy source...

This study investigates the positive coupling between the sports industry and tourism, exploring the ways to promote their interconnection. Under state guidance, the integration of sports industry services is facilitated to attract sports culture and tourism fairs, leveraging regional economic development advantages to enhance the industrial market appeal. The emerging leisure consumption mode of sports tourism injects vitality into the economy, fostering the core sports service industry. The coupling of the education and tourism sectors is strategically aligned with long-term national policies...

Cloud-based training and edge-based inference modes for Artificial Intelligence of Medical Things (AIoMT) applications suffer from accuracy degradation due to physiological signal variations among patients. On-chip learning can overcome this issue by online adaptation of neural network parameters for user-specific tasks. However, existing on-chip learning processors have limitations in terms of versatility, resource utilization, and energy efficiency. We propose HybMED, which is a novel neural signal processor that supports on-chip hybrid neural network training using a composite direct feedback alignment-based paradigm...

The utilization of Microelectromechanical Systems (MEMS) technology holds great significance for developing compact and high-performance humidity sensors in human healthcare, and the Internet of Things. However, several drawbacks of the current MEMS humidity sensors limit their applications, including their long response time, low sensitivity, relatively large sensing area, and incompatibility with a complementary metal-oxide-semiconductor (CMOS) process. To address these problems, a suspended aluminum scandium nitride (AlScN) Lamb wave humidity sensor utilizing a graphene oxide (GO) layer is firstly designed and fabricated...

Elderly falls are a major concerning threat resulting in over 1.5-2 million elderly people experiencing severe injuries and 1 million deaths yearly. Falls experienced by Elderly people may lead to a long-term negative impact on their physical and psychological health conditions. Major healthcare research had focused on this lately to detect and prevent the fall. In this work, an Artificial Intelligence (AI) edge computing based wearable device is designed and developed for detection and prevention of fall of elderly people...

The Internet offers an alternative context in which personal experiences with sexual violence can be shared. It has been suggested that victims experience lower barriers to disclosing their stories in a digital environment due to an online disinhibition effect and mainly anonymity. However, little is known about the lived experiences of victims who have shared their experiences online regarding these disinhibiting affordances of the Internet. Twenty-three interviews with victims were conducted to understand the digital affordances involved in the online disclosure of sexual victimization...

One of the biggest problems with Internet of Things (IoT) applications in the real world is ensuring data integrity. This problem becomes increasingly significant as IoT expands quickly across a variety of industries. This study presents a brand-new data integrity methodology for Internet of Things applications. The "sequence sharing" and "data exchange" stages of the suggested protocol are divided into two parts. During the first phase, each pair of nodes uses a new chaotic model for securely exchanging their identity information to generate a common sequence...

Agriculture plays a pivotal role in the economic development of a nation, but, growth of agriculture is affected badly by the many factors one such is plant diseases. Early stage prediction of these disease is crucial role for global health and even for game changers the farmer's life. Recently, adoption of modern technologies, such as the Internet of Things (IoT) and deep learning concepts has given the brighter light of inventing the intelligent machines to predict the plant diseases before it is deep-rooted in the farmlands...

In recent years, as people's living standards continue to improve, and the pace of life accelerates dramatically, the demand and quality of traditional Chinese medicine(TCM) services from patients continue to rise. As an essential supplement to the existing forms of TCM application, such as Chinese patent medicine, decoction, and formulated granules, presonalized TCM preparations is facing an increasing market demand. Currently, manual and semi-mechanized production are the primary production ways in presonalized TCM preparations...

The alignment of a receiver with a pencil beam in a wireless optical power transfer (WOPT) system employing a resonance beam charging (RBC) technology limits the establishment of a resonance cavity. Accurate tracking necessitates precise and dependable monitoring, which requires the exact placement of transmitting and receiving devices. Herein, we present a concept of a two-dimensional (2D) beam steering mechanism for RBC-based WOPT systems utilizing dispersed laser beams. The proposed approach allows a significant improvement, including reduction of scanning times and minimization of errors, in relation to conventional pencil-beam-based systems...

Due to COVID-19 pandemic the term 'Work from home (WFH), which was earlier only a theoretical concept for many, suddenly became necessary to continue various economic activities. The communication related infrastructures are often discussed in this context and how a sudden demand for it created a new avenue for certain businesses, but one very crucial aspect without which it is difficult to perform WFH is 'suitable homes' which provide necessary requirements to operate office work. This cross-sectional study focuses on investigating the issues faced by the students and working professionals who had to suddenly start working from home due to restricted movement because of lockdown measures...

Phase-change random access memory represents a notable advancement in nonvolatile memory technology; however, it faces challenges in terms of thermal stability and reliability, hindering its broader application. To mitigate these issues, doping and structural modification techniques such as phase-change heterostructures (PCH) are widely studied. Although doping typically enhances thermal stability, it can adversely affect the switching speed. Structural modifications such as PCH have struggled to sustain stable performance under high atmospheric conditions...

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In recent years, machine learning (ML) and deep learning (DL) have been the leading approaches to solving various challenges, such as disease predictions, drug discovery, medical image analysis, etc., in intelligent healthcare applications. Further, given the current progress in the fields of ML and DL, there exists the promising potential for both to provide support in the realm of healthcare. This study offered an exhaustive survey on ML and DL for the healthcare system, concentrating on vital state of the art features, integration benefits, applications, prospects and future guidelines...

Integrated circuit anti-counterfeiting based on optical physical unclonable functions (PUFs) plays a crucial role in guaranteeing secure identification and authentication for Internet of Things (IoT) devices. While considerable efforts have been devoted to exploring optical PUFs, two critical challenges remain: incompatibility with the complementary metal-oxide-semiconductor (CMOS) technology and limited information entropy. Here, we demonstrate all-silicon multidimensionally-encoded optical PUFs fabricated by integrating silicon (Si) metasurface and erbium-doped Si quantum dots (Er-Si QDs) with a CMOS-compatible procedure...

Mobile crowdsensing (MCS) systems rely on the collective contribution of sensor data from numerous mobile devices carried by participants. However, the open and participatory nature of MCS renders these systems vulnerable to adversarial attacks or data poisoning attempts where threat actors can inject malicious data into the system. There is a need for a detection system that mitigates malicious sensor data to maintain the integrity and reliability of the collected information. This paper addresses this issue by proposing an adaptive and robust model for detecting malicious data in MCS scenarios involving sensor data from mobile devices...

In the realm of the fifth-generation (5G) wireless cellular networks, renowned for their dense connectivity, there lies a substantial facilitation of a myriad of Internet of Things (IoT) applications, which can be supported by the massive machine-type communication (MTC) technique, a fundamental communication framework. In some scenarios, a large number of machine-type communication devices (MTCD) may simultaneously enter the communication coverage of a target base station. However, the current handover mechanism specified by the 3rd Generation Partnership Project (3GPP) Release 16 incurs high signaling overhead within the access and core networks, which may have negative impacts on network efficiency...

The paradigm of the Next Generation cellular network (6G) and beyond is machine-type communications (MTCs), where numerous Internet of Things (IoT) devices operate autonomously without human intervention over wireless channels. IoT's autonomous and energy-intensive characteristics highlight effective energy efficiency (EEE) as a crucial key performance indicator (KPI) of 6G. However, there is a lack of investigation on the EEE of random arrival traffic, which is the underlying platform for MTCs. In this work, we explore the distinct characteristics of F-composite fading channels, which specify the combined impact of multipath fading and shadowing...

The multi-layered negative effects caused by pollutants released into the atmosphere as a result of fires served as the stimulus for the development of a system that protects the health of firefighters operating in the affected area. A collaborative network comprising mobile and stationary Internet of Things (IoT) devices that are furnished with gas sensors, along with a remote server, constructs a resilient framework that monitors the concentrations of harmful emissions, characterizes the ambient air quality of the vicinity where the fire transpires, adopting European Air Quality levels, and communicates the outcomes via suitable applications (RESTful APIs and visualizations) to the stakeholders responsible for fire management decision making...