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Wearables are gaining prominence in the health-care industry and their use is growing. The elderly and other patients can use these wearables to monitor their vitals at home and have them sent to their doctors for feedback. Many studies are being conducted to improve wearable health-care monitoring systems to obtain clinically relevant diagnoses. The accuracy of this system is limited by several challenges, such as motion artifacts (MA), power line interference, false detection and acquiring vitals using dry electrodes. This paper aims to focus on wearable health-care monitoring systems in the literature and provides the effect of MA on the wearable system. Also presents the problems faced while tracking the vitals of users.

MA is a major concern and certainly needs to be suppressed. An analysis of the causes and effects of MA on wearable monitoring systems is conducted. Also, a study from the literature on motion artifact detection and reduction is carried out and presented here. The benefits of a machine learning algorithm in a wearable monitoring system are also presented. Finally, distinct applications of the wearable monitoring system have been explored.

According to the study reduction of MA and multiple sensor data fusion increases the accuracy of wearable monitoring systems.

This study also presents the outlines of design modification of dry/non-contact electrodes to minimize the MA. Also, discussed few approaches to design an efficient wearable health-care monitoring system.

This study aims to analyze the dynamic monitoring of deformation damage of steel structure buildings in long-term use. Although the steel structure building has the advantage of high structural strength, it will be deformed after being affected by factors such as corrosion and impact during long-term use, and which will affect building safety, especially the public building facilities. The dynamic monitoring of its security is an indispensable means.

This paper briefly introduced the principle of building information modeling (BIM)-based steel structure building information monitoring and the dynamic information monitoring system based on this principle. Then the monitoring system was used to analyze an operational steel structure suspension bridge in Xinxiang City, Henan Province, China, and compared it with the monitoring system based on back propagation (BP) neural network.

The results showed that the fitting degree of the dynamic deformation displacement data processed by BIM-based monitoring system was higher than that processed by BP-based monitoring system. Based on the comprehensive comparison of the dynamic data of all monitoring points, the BIM-based monitoring system had higher accuracy of deformation displacement monitoring and reliability of structural safety evaluation.

In summary, the BIM-based steel structure building monitoring system can effectively monitor the dynamic information of steel structure information.

The impact of mitigating flood occurrence in the rural and urban areas has become crucial as it has affected government policies for countries that are prone to flood disaster. Efforts and funds have been put up to a higher level of capabilities to ensure that coping and managing flood disaster could be resolved. Several initiatives made in managing flood are: effectively monitoring the potential at-risk inundated area, improving the river water irrigation and drainage and undertaking the environmental pollution. This chapter basically focusses more on the improvement of flood monitoring system device at the potential flood area. The approach of ubiquitous mobile SCADA offers a low-cost, portable, and small in size flood monitoring system device with easily accessible data. An easy web monitoring of environment surrounding anywhere and at any time offers a real-time data updated with a very minimum delay of each and every environment data required. There are several sensors like ultrasonic, sound, temperature and humidity, water drop and vibration sensors are equipped together with one small monitoring system platform. The alert of water level condition is notified through a beeping buzzer and light LED notation of various colors of green, yellow and red, which notify any increase of water exceeded. The platform is powered by a rechargeable battery that allows the platform to be mobile and portable. Hence, flood monitoring system platform promotes a low-cost, easy-to-handle and ubiquitous data updated device for a better monitoring system platform.

We present a model of organizational monitoring that integrates organizational justice and information privacy. Specifically, we adopt the position that the formation of invasiveness and unfairness attitudes is a goal-driven process. We employ cybernetic control theory and identity theory to describe how monitoring systems affect one's ability to maintain a positive self-concept. Monitoring provides a particularly powerful cue that directs attention to self-awareness. People draw on fairness and privacy relevant cues inherent in monitoring systems and embedded in monitoring environments (e.g., justice climate) to evaluate their identities. Discrepancies between actual and desired personal and social identities create distress, motivating employees to engage in behavioral self-regulation to counteract potentially threatening monitoring systems. Organizational threats to personal identity goals lead to increased invasiveness attitudes and a commitment to protect and enhance the self. Threats to social identity lead to increased unfairness attitudes and lowered commitment to one's organization. Implications for theory and research on monitoring, justice, and privacy are discussed along with practical implications.

As one of the most energy-intensive sectors, the manufacturing industry is strongly affected by current economic, ecological and political issues and is increasingly looking to reduce its energy consumption through effective management. One important component of energy management is monitoring, which can be improved by using the Internet of Things (IoT). This study aims to identify the factors behind the adoption of IoT energy monitoring systems in manufacturing industries and IoT’s impact on consumption in this context. Moreover, this study explores what constitutes successful implementation and develops recommendations on how companies can best use the generated energy-saving potential.

For this purpose, an exploratory, inductive research approach is taken in which five semi-structured interviews with IoT energy-monitoring platform providers located in Germany are conducted and additional documents about these platforms are analysed.

Based on these interviews and documents, this study defines the relevant factors involved in the increased adoption of IoT energy monitoring systems as desired cost reduction, regulatory requirements and customer expectations. Once implemented, a company’s energy efficiency potential strongly depends on its individual situation; however, the transparency characteristic of IoT supports managers in deriving effective energy-saving measures. Additionally, the used efficiency potential is influenced by the level of data collection and organisational capabilities.

To the best of the authors’ knowledge, as the first study, this research combines findings from the energy management and IoT research streams and places them into an organisational context. The application of the fit-viability model as an overarching framework enhances the theoretical contributions of this study. Moreover, focusing on Germany and its substantial industrial sector enables the gathering of important insights and the analysis of the specific use case of industrial IoT, which yields new findings for practitioners as well.

Nowadays, an extra consumption of electric energy in the Colombian houses is generated due to electric or electronic elements plugged into the electric network. This fact produces a cost overrun in the user’s electricity bills. To reduce this extra cost, and also with a plus of reducing greenhouse gas emission, a monitoring system for the consumption of electric energy in a household will be designed and implemented to make electricity users realize how much money and energy is being wasted due to the unnecessary electric elements plugged into the network. This paper aims to show a monitoring system that allows the client to supervise the consumption of some appliances inside his/her home, remotely. It is also considered the HMI to be able to log in, choose the intervals of data and generate reports and graphics. The monitoring system is based on the integration of several technologies that are already used and implemented in houses and buildings, such as: measuring and treatment of data electronically using microcontrollers, Wi-Fi technology and dynamic graphic interface (website).

The methodology consists of several tasks, starting from documentation of the variables, instrumentation and methods for getting to the solution; the first part of the methodology focuses on selecting the electric and/or electronic elements to be monitored, so the instrumentation is able to monitor. Then, the power stage was implemented in this stage to measure signals from the sensors while sensing the electric nodes are adjusted, so does the transmission and reception. In the third stage, the design information system was implemented; this is where the received data from the sensors are stored and managed for further organization and visualization. Activities included the following: Analysis of the model of use cases: Identification of actors and actions that are involved in the system. Server selection: Study of the different server to manage the database. Design of the database: The variables, tables, fields, profiles are determined for managing the information. Connection between sensors and database: Correct data transmission and managing to the database from the sensors. Finally, the system is validated in a rural house for a month.

The monitoring system satisfies the main objective of making a tracing of the behavior of some appliances inside a house, showing graphically the instant current generated while connected, the cumulated energy consumed and the cost in Colombian pesos of the energy consumed so far, in real time.

The monitoring system requires the correct functioning of the sensors connected to each household appliance in the home.

The main approach in the monitoring platform is the real-time measurement of energy consumption by nodes (in each appliance) that allows the user to control the money. The innovative impact of the project will be based on the use of hardware and information systems in the measurement of electrical consumption.

This research has a direct impact on the economic aspects of the low-income population by allowing them to manage their energy consumption through the proposed system.

The main approach in the monitoring platform is the real-time measurement of energy consumption by nodes (in each appliance) that allows the user to control the money.

The aim of this evaluation was to carry out an evaluation of the Just Checking activity monitoring system, which supports people with dementia in their own homes. The study was carried out with Warwickshire County Council's social services, and a number of their service users. The system was installed in the homes of six people with dementia, and used by their family carers and care professionals, whose experiences were gathered in semi‐structured interviews. In total 15 people took part in interviews, including two of the people with dementia.The system gave family carers and professionals a better insight into the activities of the person with dementia, and how they were managing in their own homes. The majority of users were surprised at the consistency of the daily pattern of activity of the person with dementia and, as a result, their view of the capabilities of the person changed. The data from the system reassured family carers and proved a useful assessment tool for professionals on which to plan care.Contrary to expectations, the monitoring system gave people with dementia more control of their lives by providing a means by which they could communicate their capabilities in their home environment.

Performance monitoring systems are typically designed to assess the achievement of a single program or agency. In recent years, there have been efforts to integrate programs addressing a particular policy area (e.g., workforce development). The evolving systems incorporate multiple programs, agencies, funding streams, service providers, information systems, and goals. The design of integrated performance monitoring systems requires applying measures, standards, and comparisons to multiple levels of assessment. The author differentiates between traditional and integrated performance monitoring systems, identifies the levels that must be addressed by integrated systems and the obstacles that must be overcome in developing them, and discusses the benefits of integrated performance monitoring systems.

Human–robot collaboration (HRC) is on the rise in a bid for improved flexibility in production cells. In the context of overlapping workspace between a human operator and an industrial robot, the major cause for concern rests on the safety of the former.

In light of recent advances and trends, this paper proposes to implement a monitoring system for the shared workspace HRC, which supplements the robot, to locate the human operator and to ensure that at all times a minimum safe distance is respected by the robot with respect to its human partner. The monitoring system consists of four neural networks, namely, an object detector, two neural networks responsible for assessing the detections and a simple, custom speech recognizer.

It was observed that with due consideration of the production cell, it is possible to create excellent data sets which result in promising performances of the neural networks. Each neural network can be further improved by using its mistakes as examples thrown back in the data set. Thus, the whole monitoring system can achieve a reliable performance.

Success of the proposed framework may lead to any industrial robot being suitable for use in HRC.

This paper proposes a system comprising neural networks in most part, and it looks at a digital representation of the workspace from a different angle. The exclusive use of neural networks is seen as an attempt to propose a system which can be relatively easily deployed in industrial settings as neural networks can be fine-tuned for adjustments.

The purpose of this paper is to investigate a dystopian situation with special reference to how a panoptic monitoring system emerges in schools. To satisfy this aim, there will be a close analysis of the city of Nago in Okinawa Prefecture, where there is a huge debate over the new US Marine base construction and how it greatly influences people’s lives.

This study will employ a self-study by the first author, who is a clinical psychologist under the board of education in the city. This self-study aims to examine the lived experiences of the author based on interactions with critical friends.

The government’s selection of the site for the new base created a schism in the community, and the introduction of compensations led to the establishment of a communal panoptic monitoring system. This communal panoptic monitoring largely influences the relationships between pupils, teachers and parents. Further, another panoptic monitoring system has developed inside the Nago schools due to the intensification of the assessment policies given by the ministry in Tokyo.

This investigation purports to analyse a dystopian situation with special reference to how a panoptic monitoring system, a key element of a dystopia, emerges in schools.