https://pure.rug.nl/ws/files/2357318/2013EnergyBuildingsNguyen.pdf

Energy intelligent buildings based on user activity: A survey

The purpose of this paper is to explore how rising technologies from Industry 4.0 can be integrated with circular economy (CE) practices to establish a business model that reuses and recycles wasted material such as scrap metal or e-waste.,The qualitative research method was deployed in three stages. Stage 1 was a literature review of concepts, successful factors and barriers related to the transition towards a CE along with sustainable supply chain management, smart production systems and additive manufacturing (AM). Stage 2 comprised a conceptual framework to integrate and evaluate the synergistic potential among these concepts. Finally, stage 3 validated the proposed model by collecting rich qualitative data based on semi-structured interviews with managers, researchers and professors of operations management to gather insightful and relevant information.,The outcome of the study is the recommendation of a circular model to reuse scrap electronic devices, integrating web technologies, reverse logistics and AM to support CE practices. Results suggest a positive influence from improving business sustainability by reinserting waste into the supply chain to manufacture products on demand.,The impact of reusing wasted materials to manufacture new products is relevant to minimising resource consumption and negative environmental impacts. Furthermore, it avoids hazardous materials ending up in landfills or in the oceans, seriously threatening life in ecosystems. In addition, reuse of wasted material enables the development of local business networks that generate jobs and improve economic performance.,First, the impact of reusing materials to manufacture new products minimises resource consumption and negative environmental impacts. The circular model also encourages keeping hazardous materials that seriously threaten life in ecosystems out of landfills and oceans. For this study, it was found that most urban waste is plastic and cast iron, leaving room for improvement in increasing recycling of scrap metal and similar materials. Second, the circular business model promotes a culture of reusing and recycling and motivates the development of collection and processing techniques for urban waste through the use of three-dimensional (3D) printing technologies and Industry 4.0. In this way, the involved stakeholders are focused on the technical parts of recycling and can be better dedicated to research, development and innovation because many of the processes will be automated.,The purpose of this study was to explore how Industry 4.0 technologies are integrated with CE practices. This allows for the proposal of a circular business model for recycling waste and delivering new products, significantly reducing resource consumption and optimising natural resources. In a first stage, the circular business model can be used to recycle electronic scrap, with the proposed integration of web technologies, reverse logistics and AM as a technological platform to support the model. These have several environmental, sociotechnical and economic implications for society.,The sociotechnical aspects are directly impacted by the circular smart production system (CSPS) management model, since it creates a new culture of reuse and recycling techniques for urban waste using 3D printing technologies, as well as Industry 4.0 concepts to increase production on demand and automate manufacturing processes. The tendency of the CSPS model is to contribute to deployment CE in the manufacture of new products or parts with AM approaches, generating a new path of supply and demand for society.

Exploring Industry 4.0 technologies to enable circular economy practices in a manufacturing context: A business model proposal

The past few years have witnessed an increase in the development of wearable sensors for health monitoring systems. This increase has been due to several factors such as development in sensor technology as well as directed efforts on political and stakeholder levels to promote projects which address the need for providing new methods for care given increasing challenges with an aging population. An important aspect of study in such system is how the data is treated and processed. This paper provides a recent review of the latest methods and algorithms used to analyze data from wearable sensors used for physiological monitoring of vital signs in healthcare services. In particular, the paper outlines the more common data mining tasks that have been applied such as anomaly detection, prediction and decision making when considering in particular continuous time series measurements. Moreover, the paper further details the suitability of particular data mining and machine learning methods used to process the physiological data and provides an overview of the properties of the data sets used in experimental validation. Finally, based on this literature review, a number of key challenges have been outlined for data mining methods in health monitoring systems.

/pdf/data-mining-for-wearable-sensors-in-health-monitoring-13a1q3cm4g.pdf

Data Mining for Wearable Sensors in Health Monitoring Systems: A Review of Recent Trends and Challenges

Industry 4.0: A bibliometric analysis and detailed overview

Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

An end-to-end Internet of Things solution for Reverse Supply Chain Management in Industry 4.0

The adoption of internet of things in a circular supply chain framework for the recovery of WEEE: the case of lithium-ion electric vehicle battery packs.

This paper encourages the cooperation of different Internet of Things technologies in industrial environments for avoiding social disruption in novel Industry 4.0 paradigms. For this, green I3A smart factory (GreenISF) scenario is presented, where the deployment of a collaborative mesh network based on Bluetooth low energy (BLE) and long range wide-area network (LoRaWAN) technologies promotes human–machine collaboration towards socially sustainable factories. In order to encourage human-centric architectures in such environments, our smart wristband prototype OperaBLE is introduced in this paper as key enabler for human-in-the-loop systems. Thus, the network deployed in GreenISF is composed of body area networks which monitor labor activity and reinforce security at work by embedding sensors in regulatory industrial clothes. These networks cooperate with our BLE mesh infrastructure aimed to fulfill the major challenges Industry 4.0: zero fails, total coverage, and sustainability. Furthermore, a context information network based on LoRaWAN complements our mesh network to provide the system with valuable environmental data and prevent operators from harmful workplaces. The system is connected to a fog server responsible for preprocessing raw data that will be stored in a global cloud server. The experiments carried out highlight the contribution of OperaBLE towards safer working conditions and a sustainable digitalization of Industry 4.0.

IoT Heterogeneous Mesh Network Deployment for Human-in-the-Loop Challenges Towards a Social and Sustainable Industry 4.0

Current sensor networks need to be improved and updated to satisfy new essential requirements of the Internet of Things, where cutting-edge applications will appear. These requirements are: total coverage, zero fails (high performance), scalability and sustainability (hardware and software). We are going to evaluate Bluetooth Low Energy as wireless transmission technology and as the ideal candidate for these improvements, due to its low power consumption, its low cost radio chips and its ability to communicate with users directly, using their smartphones or smartbands. However, this technology is relatively recent, and standard network topologies are not able to fulfil its new requirements. To address these shortcomings, the implementation of other more flexible topologies (as the mesh topology) will be very interesting. After studying it in depth, we have identified certain weaknesses, for example, specific devices are needed to provide network scalability, and the need to choose between high performance or sustainability. In this paper, after presenting the studies carried out on these new technologies, we propose a new packet format and a new BLE mesh topology, with two different configurations: Individual Mesh and Collaborative Mesh. Our results show how this topology improves the scalability, sustainability, coverage and performance.

From Sensor Networks to Internet of Things. Bluetooth Low Energy, a Standard for This Evolution.

The task of routing data from a source to the sink is a critical issue in ad hoc and wireless sensor networks. In this paper, the use of fuzzy logic to perform role assignment during route establishment and maintenance is proposed. An incremental approach is presented and compared with similar existing routing protocols. Efficient routing approaches provide network load balance to extend network lifetime, efficiency improvements, and data loss avoidance. Experiments show promising results for our proposals and its suitability for operating with dense networks, obtaining quick route creation as well as energy efficiency.

Teresa Olivares

Papers

An end-to-end Internet of Things solution for Reverse Supply Chain Management in Industry 4.0

The adoption of internet of things in a circular supply chain framework for the recovery of WEEE: the case of lithium-ion electric vehicle battery packs.

IoT Heterogeneous Mesh Network Deployment for Human-in-the-Loop Challenges Towards a Social and Sustainable Industry 4.0

From Sensor Networks to Internet of Things. Bluetooth Low Energy, a Standard for This Evolution.

Fuzzy-logic based routing for dense wireless sensor networks