Internet of Things (IoT) technology has attracted much attention in recent years for its potential to alleviate the strain on healthcare systems caused by an aging population and a rise in chronic illness. Standardization is a key issue limiting progress in this area, and thus this paper proposes a standard model for application in future IoT healthcare systems. This survey paper then presents the state-of-the-art research relating to each area of the model, evaluating their strengths, weaknesses, and overall suitability for a wearable IoT healthcare system. Challenges that healthcare IoT faces including security, privacy, wearability, and low-power operation are presented, and recommendations are made for future research directions.

Internet of Things for Smart Healthcare: Technologies, Challenges, and Opportunities

The Health Insurance Portability and Accountability Act, also known as HIPAA, was first delivered to congress in 1996 and consisted of just two Titles. It was designed to protect health insurance coverage for workers and their families while between jobs. It establishes standards for electronic health care transactions and addresses the issues of privacy and security when dealing with Protected Health Information (PHI). HIPAA is applicable only in the United States of America.

The Health Insurance Portability and Accountability Act.

The advancement of technologies over years has poised Internet of Things (IoT) to scoop out untapped information and communication technology opportunities. It is anticipated that IoT will handle the gigantic network of billions of devices to deliver plenty of smart services to the users. Undoubtedly, this will make our life more resourceful but at the cost of high energy consumption and carbon footprint. Consequently, there is a high demand for green communication to reduce energy consumption, which requires optimal resource availability and controlled power levels. In contrast to this, IoT devices are constrained in terms of resources—memory, power, and computation. Low power wide area (LPWA) technology is a response to the need for efficient utilization of power resource, as it evinces characteristics such as the capability to proffer low power connectivity to a huge number of devices spread over wide geographical areas at low cost. Various LPWA technologies, such as LoRa and SigFox, exist in the market, offering a proficient solution to the users. However, in order to abstain the need of new infrastructure (like base station) that is required for proprietary technologies, a new cellular-based licensed technology, narrowband IoT (NBIoT), is introduced by 3GPP in Rel-13. This technology presents a good candidature to handle LPWA market because of its characteristics like enhanced indoor coverage, low power consumption, latency insensitivity, and massive connection support towards NBIoT. This survey presents a profound view of IoT and NBIoT, subsuming their technical features, resource allocation, and energy-efficiency techniques and applications. The challenges that hinder the NBIoT path to success are also identified and discussed. In this paper, two novel energy-efficient techniques “zonal thermal pattern analysis” and energy-efficient adaptive health monitoring system have been proposed towards green IoT.

A Survey on Energy Efficient Narrowband Internet of Things (NBIoT): Architecture, Application and Challenges

How Machine Learning Will Transform Biomedicine

In the early months of the COVID-19 pandemic with no designated cure or vaccine, the only way to break the infection chain is self-isolation and maintaining the physical distancing. In this article, we present a potential application of the Internet of Things (IoT) in healthcare and physical distance monitoring for pandemic situations. The proposed framework consists of three parts: a lightweight and low-cost IoT node, a smartphone application (app), and fog-based Machine Learning (ML) tools for data analysis and diagnosis. The IoT node tracks health parameters, including body temperature, cough rate, respiratory rate, and blood oxygen saturation, then updates the smartphone app to display the user health conditions. The app notifies the user to maintain a physical distance of 2 m (or 6 ft), which is a key factor in controlling virus spread. In addition, a Fuzzy Mamdani system (running at the fog server) considers the environmental risk and user health conditions to predict the risk of spreading infection in real time. The environmental risk conveys from the virtual zone concept and provides updated information for different places. Two scenarios are considered for the communication between the IoT node and fog server, 4G/5G/WiFi, or LoRa, which can be selected based on environmental constraints. The required energy usage and bandwidth (BW) are compared for various event scenarios. The COVID-SAFE framework can assist in minimizing the coronavirus exposure risk.

/pdf/covid-safe-an-iot-based-system-for-automated-health-2uv2b59ty2.pdf

COVID-SAFE: An IoT-Based System for Automated Health Monitoring and Surveillance in Post-Pandemic Life

The authors' context-aware interactive mobile-health (m-health) system (ImHS) provides real-time, two-way communication between diabetes patients and caregivers by utilizing Internet of Things (IoT) technology. When a diabetic patient records abnormal blood sugar values during measurement, the ImHS sends a reminder to the patient and caregivers, motivating behavior change and improving the quality of chronic care. The ImHS features user-friendly interfaces for patients, family, and professional caregivers that lets them rapidly understand the patient's health status. In this study, the authors look at ImHS use in diabetes care. However, the ImHS can be easily adapted for integration into other healthcare systems.

A Context-Aware, Interactive M-Health System for Diabetics

The authors designed an interactive telecare system (ITCS) enhanced by Internet of Things (IoT) technology that enables direct communication between patients' medical devices and caregivers' smartphones to improve the quality of care for chronically ill patients. This system can remotely activate hardware components of medical devices in real time to access current information and smartphones via a telecare application. A case study was constructed with 2.5G blood glucose monitors (BGMs) integrated with a cloud platform and with Android and iOS telecare applications. Overseas medical institutions have confirmed the system's potential value in chronic-illness treatment regimens and have provided useful feedback.

An Interactive Telecare System Enhanced with IoT Technology

Articles posted on a forum often contain new Internet terms related to opinion elements. Consequently, existing Chinese opinion-mining systems may exhibit low recall and precision because they cannot recognize these new Internet terms. Therefore, we designed an algorithm to elaborate on the opinion elements of such articles by extracting the new terms. By ignoring any uncommon opinion element that appears only once, we determine whether the new term identified through manual judgment is a useful opinion element for a specific domain and add it to the thesaurus. In comparison with semi-automatic annotation methods, our approach can save considerable labor. The same Chinese word may have different meanings depending on the context, and this fact is prone to cause difficulties by changing the polarity or meaning of certain opinion elements, leading to errors in the analysis results of many Chinese systems. We designed appropriate algorithms to address this problem. Meanwhile, this system extracts the opinion elements from an article based on its established thesaurus and simultaneously considers various sentence patterns, the default topic, and clause priority to determine the opinion tendency of the author.

Extracting New Opinion Elements in the Semi-automatic Chinese Opinion-Mining System from Internet Forums

At present, pesticide residue testing is done by professionals in the laboratory, because test results are not fast enough for market demand. The process of taking data is cumbersome and error-prone; although some operators have developed wireless pesticide residue detectors. But its' Internet of Things (IoT) system can only upload detection results to the database, and does not carry out subsequent analysis or provide warning services. This study will redesign and implement an IoT pesticide residue detection system, which will allow users to view the detection results through the webpage and mobile app after uploading those results. At the same time, when there are some abnormal situations like missing spare parts or getting abnormal detection results, this system will automatically send a warning message to the relevant person's mobile phone, so the users can fix errors as soon as possible. Besides, this study also designed a sharing function; this function allows users to set conditions to list the filtered detection results, and automatically send the QR code and website address of the detection results list to the user mailbox. Finally, the user can send the QR code or website to other relevant personnel for confirmation of detection results. 

Design and implementation of pesticide residues detection system

ABSTRACT When a stock portfolio is suggested to inventors, they may need a mechanism to replace stocks when their future prospects are pessimistic. However, existing approaches only consider all assets to find a diverse group stock portfolio (DGSP), which may suffer massive losses as a result. In this paper, an intelligent optimisation algorithm is proposed to obtain a more profitable DGSP with active and inactive stocks. In the coding scheme, not only grouping, stocks, and weighting but also active stock parts are used to represent a DGSP. Two evaluation functions are developed according to five factors, including group balance, modified portfolio satisfaction, price balance, unit balance, and extended diversity factor. These functions are used to assess the fitness of a chromosome. Finally, empirical studies were conducted on two financial datasets to show the merits of the proposed algorithm.

Rui-Dong Chiang

Papers

A Context-Aware, Interactive M-Health System for Diabetics

An Interactive Telecare System Enhanced with IoT Technology

Extracting New Opinion Elements in the Semi-automatic Chinese Opinion-Mining System from Internet Forums

Design and implementation of pesticide residues detection system

An evolutionary-based approach for optimising diverse group stock portfolio with active and inactive stocks