Design a Remote Patient Health Monitoring System (RPHMS) Using IoT

Healthcare has become one of the principal issue with the rise in human population and medical expenditure. For a healthy life, it is essential to follow human body’s vital signals. Continuous Monitoring of patient’s vital signals cannot be provided outside hospital. As it is hard to monitor the patient’s condition for 24 hours, it was proposed in this paper to observe continuously the condition of patient despite the patient being busy with his routine and to screen the health status to the doctors through Internet of Things. This paper proposes health monitoring system using non-intrusive biomedical sensors that measure five parameters like ECG, SPO2, toxic gas, temperature and blood pressure. Proposed method makes use of Arduino Uno Controller to which non-invasive biomedical sensors are connected. The output is displayed on any digital monitoring system using Arduino Uno. The data obtained from the sensors is uploaded to the Thing Speak cloud to store and to access patient’s information by their doctors or by the concerned for necessary follow-ups in real-time. IoT is a powerful domain where sensors can connect and data is viewed over the Internet.

Smart Digital Monitoring Tool

Smart Digital Monitoring Tool As the world is currently going through a wave of rapid digital transformations, finding digital solutions in the oil and gas industry today is more important than ever. Not only is digital transformation one of the main pillars needed to embrace the Fourth Industrial Revolution (IR 4.0), but it is also indispensable to achieve operational excellence. By connecting process parameters and physical assets with digital monitoring tools, more accurate insights can be gained, which enables real-time responses to challenges and proactive corrective actions. Different tools and multiple dashboards have been employed to monitor different focus areas such as crude quality, environmental performance, energy consumption, and critical process parameters and chemicals consumption. In spite of the several available tools to monitor and summarize the facilities performance and key performance indicators (KPIs), taking quick and proactive actions to resolve the issues and improve the performance remains challenging sometimes. This is because for digital transformation to have a stronger impact, it better be integrated across the whole business focus area. This means that a single and comprehensive tool will help identify areas for improvement — timely and quickly by the Operations, Maintenance and Engineering (OME) team. In line with Saudi Aramco's Operational Excellence (OE) program, and to produce oil and gas in an efficient, cost-effective, reliable and responsible manner, a comprehensive and creative smart tool has been developed to deliver energy with better quality, enhanced safety, improved reliability, continuous sustainably, and increased efficiency.

Securing Environmental IoT Data Using Masked Authentication Messaging Protocol in a DAG-Based Blockchain: IOTA Tangle

The demand for the digital monitoring of environmental ecosystems is high and growing rapidly as a means of protecting the public and managing the environment. However, before data, algorithms, and models can be mobilized at scale, there are considerable concerns associated with privacy and security that can negatively affect the adoption of technology within this domain. In this paper, we propose the advancement of electronic environmental monitoring through the capability provided by the blockchain. The blockchain’s use of a distributed ledger as its underlying infrastructure is an attractive approach to counter these privacy and security issues, although its performance and ability to manage sensor data must be assessed. We focus on a new distributed ledger technology for the IoT, called IOTA, that is based on a directed acyclic graph. IOTA overcomes the current limitations of the blockchain and offers a data communication protocol called masked authenticated messaging for secure data sharing among Internet of Things (IoT) devices. We show how the application layer employing the data communication protocol, MAM, can support the secure transmission, storage, and retrieval of encrypted environmental sensor data by using an immutable distributed ledger such as that shown in IOTA. Finally, we evaluate, compare, and analyze the performance of the MAM protocol against a non-protocol approach.

Tracking Infant Development With a Smartphone: A Practical Guide to the Experience Sampling Method

The COVID-19 pandemic has forced developmental researchers to rethink their traditional research practices. The growing need to study infant development at a distance has shifted our research paradigm to online and digital monitoring of infants and families, using electronic devices, such as smartphones. In this practical guide, we introduce the Experience Sampling Method (ESM) – a research method to collect data, in the moment, on multiple occasions over time – for examining infant development at a distance. ESM is highly suited for assessing dynamic processes of infant development and family dynamics, such as parent-infant interactions and parenting practices. It can also be used to track highly fluctuating family dynamics (e.g., infant and parental mood or behavior) and routines (e.g., activity levels and feeding practices). The aim of the current paper was to provide an overview by explaining what ESM is and for what types of research ESM is best suited. Next, we provide a brief step-by-step guide on how to start and run an ESM study, including preregistration, development of a questionnaire, using wearables and other hardware, planning and design considerations, and examples of possible analysis techniques. Finally, we discuss common pitfalls of ESM research and how to avoid them.

Dynamic Quality Monitoring System to Assess the Quality of Asphalt Concrete Pavement

With the rapid development of new technologies, such as big data, the Internet of Things (IoT) and intelligent sensing, the traditional asphalt pavement construction quality evaluation method has been unable to meet the needs of road digital construction. At the same time, the development of such technologies enables a new management system for asphalt pavement construction. In this study, firstly, the dynamic quality monitoring system of asphalt concrete pavement is established by adopting the BeiDou Navigation Satellite System, intelligent sensing, the IoT and 5G technology. This allows key technical indicators to be collected and transmitted for the whole process of asphalt mixture, which includes the mixing plant, transport vehicle, paving and compaction. Secondly, combined with AHP and the entropy weight (EW) method, the index combination weight is calculated. The comprehensive index for the pavement digital construction quality index (PCQ) is proposed to reflect the impact of monitoring indicators on pavement quality. An expert decision-making model is formed by using the improved particle swarm optimization (PSO) algorithm coupled with radial basis function neural network (RBF). Finally, the digital monitoring index and pavement performance index are connected to establish a full-time and multi-dimensional digital construction quality evaluation model. This study is verified by a database created from the digital monitoring data of pavement construction collected from a highway construction project. The system proposed in this study can accurately reflect the quality of pavement digital construction and solve the lag problem existing in the feedback of construction site.

Burnout digital monitoring on employee engagement at the company

Burnout is a condition of mental, and physical fatigue of a worker caused by a person's professional life. Engagement is the attachment that exists in an employee to a job where the employee works. The relationship between burnout and engagement in a company significantly affects the employees' performance and the company's results. This study aims to digitally record burnout, and engagement that exists in a company in improving its product quality. Digital-based monitoring is one of the tools that can be used to monitor employee performance activities in a measured manner to produce information that companies can use in decision-making. The method used quantitative research method approach using LISREL. Results achieved several variables that affect burnout and engagement related to employee work at that company. Implications for companies with the existence of employee digital data minimize burnout and increase employee engagement in the company. This digital data can be used as accurate information in looking at the condition of employees in a company.

Artificial Negative Polarity Thunderstorm Cell Modeling of Nearby Incomplete Upward Discharges’ Influence on Elements of Monitoring Systems for Air Transmission Lines

The article represents results of a physical simulation of incomplete upward leader discharges induced on air transmission lines’ elements, using charged artificial thunderstorm cells of negative polarity. The influence of such discharges on closely located model sensors (both of rod and elongated types) of digital monitoring systems, as well as on the models of receiver-transmission systems of local data collection (antennas), was determined. Effect of heterogeneity of electromagnetic field caused by incomplete upward discharges on frequency specter of signals generated on sensors and antennas was estimated. Wavelet analysis was carried out to determine the basic frequency diapasons of such signals. Based on experimental data obtained, suppositions about the extent of influence of nearby incomplete leader discharges on the functioning of currently used systems of transmission lines’ monitoring were made.