Opportunities and challenges for location aware computing in the construction industry

This paper describes the opportunities for location aware computing to enhance information capture and use within the construction industry. The construction industry is characterized as being slow to take up innovative mobile ICT, despite the highly mobile workforce who must collaborate with a range of on and off-site personnel, and make use of large volumes of information. Based on fieldwork and workshop activities within COMIT (a large-scale mobile IT project within the construction industry), the information used within two key business processes – health and safety audits, and site design problem resolution – is outlined, and the opportunities for support by location aware computing discussed. Some potential challenges are also identified, as is the need to understand how to provide real value (as opposed to just information) to the end user

An innovative mobile application for construction programme managers

Construction programme management is a complex and information-intensive environment. The construction programme management team requires access to construction information in real-time and when needed. The current increasing use of mobile devices offers an opportunity to meet this need. The efficient management of construction programmes is one of the major factors for improving stakeholders’ satisfaction. An innovative tool is needed in accessing the right information at the right time, especially when spontaneous and urgent decision-making is needed. To this end, the innovative use of a mobile device in delivering information and services to the management team in real-time and based on their current context offers significant benefits. This paper discusses context-aware computing, the enabling technologies for geolocation and the development of a prototype, mobile, context-aware application for construction programme management. The prototype system developed is based on the findings from an earlier study of user requirements which showed that the ability to provide relevant information and services at an appropriate time and at the most appropriate location has the potential to improve the monitoring and control of construction programmes. The prototype system demonstrates the provision of context-specific information and services to construction programme managers using a mobile device. The benefits and limitations of the proposed approach are discussed and conclusions drawn about the potential impact of enhanced information delivery for the efficiency of the construction programme managers

The Emerging Internet of Things Marketplace From an Industrial Perspective: A Survey

The Internet of Things (IoT) is a dynamic global information network consisting of internet-connected objects, such as Radio-frequency identification (RFIDs), sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future internet. Over the last decade, we have seen a large number of the IoT solutions developed by start-ups, small and medium enterprises, large corporations, academic research institutes (such as universities), and private and public research organisations making their way into the market. In this paper, we survey over one hundred IoT smart solutions in the marketplace and examine them closely in order to identify the technologies used, functionalities, and applications. More importantly, we identify the trends, opportunities and open challenges in the industry-based the IoT solutions. Based on the application domain, we classify and discuss these solutions under five different categories: smart wearable, smart home, smart, city, smart environment, and smart enterprise. This survey is intended to serve as a guideline and conceptual framework for future research in the IoT and to motivate and inspire further developments. It also provides a systematic exploration of existing research and suggests a number of potentially significant research directions.Comment: IEEE Transactions on Emerging Topics in Computing 201

Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Robots, drugs, reality and education: how the future will change how we think

Emerging technologies for learning report - Article exploring various future trends and their potential impact on educatio

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0