Cloud Computing and Internet of Things: Issues and Developments

Cloud computing is a pervasive paradigm that is growing by the day. Various service types are gaining increased importance. Internet of things is a technology that is developing. It allows connectivity of both smart and dumb systems over the internet. Cloud computing will continue to be relevant to IoT because of scalable services available on the cloud. Cloud computing is the need for users to procure servers, storage, and applications. These services can be paid for and utilized using the various cloud service providers. Clearly, IoT which is expected to connect everything to everyone, requires not only connectivity but large storage that can be made available either through on-premise or off-premise cloud facility. On the other hand, events in the cloud and IoT are dynamic. This paper aims to provide an understanding of cloud and IoT. In addition, the paper discusses current trends in terms of industry activities. It also examines the prospects of cloud and IoT trends in cloud application management. This will be of benefit to prospective cloud users and even cloud providers

Health Building Information Modeling (HBIM)-based Facility Management: A Conceptual Framework

The outbreak of the COVID-19 epidemic has brought significant challenges to building operation and occupant health. In practice, building operators have begun to use various Internet of Things (IoT) technologies, intelligent sensing devices, and manual registration methods to update occupant information and behaviour in different building areas. Building spaces are classified according to their health, such as the distinction between safe areas and infected areas. Using the health data of occupants and spaces to help buildings operate efficiently and safely is a problem that needs to be solved urgently. This research proposed a conceptual framework for facility management driven by a Health Building Information Model (HBIM). The framework aims to incorporate the emerging data types to enrich the health information of the BIM model and provide decision support for facility operation and maintenance

Controlled and Secure Access to Promote the Industrial Internet of Things

Internet of Things (IoT) aims at facilitating access to all devices that are connected to the internet, both wired and wireless. This scenario can initially seem interesting. Nevertheless, it has a lack of privacy and danger of malicious interaction with the devices. Therefore, IoT, as it stands, is not suitable for companies to make their data and devices accessible through the internet, since they could find an untidy cloud, made up of devices without the necessary control of use. This paper proposes the use of the cloud computing advantages to develop a secure access global system based on a cloud. The company will decide the controlled access to the chosen devices and data, both by employees and external people. The developed system can be used from different scenarios such as: a public cloud; an Infrastructure as a Service (IaaS); and a private cloud. To illustrate the operation of the developed system, a representative network of heterogeneous multiprotocol devices has been designed

Machine Learning Framework for the Sustainable Maintenance of Building Facilities

The importance of sustainable building maintenance is growing as part of the Sustainable Building concept. The integration and implementation of new technologies such as the Internet of Things (IoT), smart sensors, and information and communication technology (ICT) into building facilities generate a large amount of data that will be utilized to better manage the sustainable building maintenance and staff. Anomaly prediction models assist facility managers in informing operators to perform scheduled maintenance and visualizing predicted facility anomalies on building information models (BIM). This study proposes a Machine Learning (ML) anomaly prediction model for sustainable building facility maintenance using an IoT sensor network and a BIM model. The suggested framework shows the data management technique of the anomaly prediction model in the 3D building model. The case study demonstrated the framework’s competence to predict anomalies in the heating ventilation air conditioning (HVAC) system. Furthermore, data collected from various simulated conditions of the building facilities was utilized to monitor and forecast anomalies in the 3D model of the fan coil. The faults were then predicted using a classification model, and the results of the models are introduced. Finally, the IoT data from the building facility and the predicted values of the ML models are visualized in the building facility’s BIM model and the real-time monitoring dashboard, respectively

BIM-Based Life Cycle Sustainability Assessment for Buildings

In recent years, the progress of digitization in the architecture and construction sectors has produced enormous advances in the automation of analysis and evaluation processes. This is the case with environmental analysis systems, such as the life cycle analysis. Methodology practitioners have found a fundamental ally in the building information modeling platforms, which allow tasks that conventionally consume large amounts of energy and time to be carried out more automatically and efficiently. In this publication, the reader will find some of the latest advances in this area