Intelligent OPC Building Information Management System Based on IoT

With the rapid development of artificial intelligence, computers and Internet of Things technologies, building intelligence is becoming more and more popular. However, as the various functional subsystems and equipment of intelligent buildings are connected to each other, the traditional management system needs to monitor and modulate more and more programs, which will have a great impact on the interoperability of the subsystems. Therefore, a more complete and powerful management system is needed. OPC provides a unified standard that can effectively solve this problem. Therefore, the purpose of this article is to design an intelligent OPC building information management system based on the Internet of Things. This article first summarizes the development history and status quo of OPC technology, and then extends the design principles of building information management system based on OPC. Based on its design principles, a detailed analysis of the various subsystems of the building information management system, such as fire protection, intrusion prevention, monitoring, access control, and central air conditioning, is carried out. This article systematically explained the application of PID in the building information management system. And use comparative analysis method, observation method and other research forms to conduct experimental research on the intelligent OPC building information management system based on computer Internet of things. The research shows that compared with the traditional building management system, the intelligent OPC-based building management system researched in this paper can transmit information faster and have higher accuracy.

Implementing Building Information Management (BIM) In Estonian Transport Administration

Digitalisation is the key to efficiency in the road construction Industry. Building Information Management (BIM), being the main developments in the architecture, engineering, and construction (AEC) Industry, offers a technology as well as processes to bring traditional design and construction practices to the digital era. Estonian Road Administration started the process of BIM implementation to the Estonian road Industry in 2017, when the first planning of pilot projects began. Today, the utilisation of BIM is set as a strategic goal for Estonian Transport Administration (formerly Estonian Road Administration) and a structured approach has been developed in order to overcome such a complex shift in the ways, how road information is being managed in the whole life cycle of a road. Development of principles of data movement, setting technical guidelines and requirements, managing legal issues and communication within the organisation, as well as outside, training of personnel are all aspects that need to be taken into consideration. Successful adaption also needs good communication with the Industry, which is mainly done with Estonian Digital Construction Cluster – a collaboration which brings together the main stakeholders in the sector. In a few years time most of the main sections of the road life cycle will hopefully utilise BIM successfully in Estonia, but the key lies within a well developed and excecuted implementation. The paper describes the development of such a implementation plan and also brings out the main issues and success factors, that are relevant for a successful shift towards digitalisation in the road construction industry.

Noise in Maternity Wards: A Research on Its Contributors and Sources

Aims: This research aimed to investigate the major user behavior patterns of noise sources in healthcare environments and summarize such information as evidence that can inform the design of maternity wards for indoor noise control and patients’ well-being. Methods: Field investigations were conducted to identify users’ behaviors as the major contributors of noises in the maternity wards of a typical hospital. A control experiment was set to test the feasibility of a noise control system that consisted of smart bracelets, mobile terminals, and monitors. Comparative studies were designed for statistical analysis of patients’ sleep quality and satisfaction. Finally, a follow-up interview was conducted among the experts who were from the fields of healthcare environment design, medical treatments, and hospital administration to shed an insight into their concerns on the findings. Results: The enclosed waiting areas, instead of open ones that were often seen in hospitals, around the entrances of operation rooms, were considered as the appropriate design strategy for maternity wards in China. Such a design could keep patients from being exposed to the excessive noises generated by visitors during nighttime, although it would occupy the floor area of wards and lead to a reduction of beds. Moreover, the statistical information of patients’ behaviors could be used to moderate visitors’ behaviors. Conclusions: It was necessary to include user behavior information in building information management and then make a good trade-off between the proportions of wards and enclosed waiting rooms in order to achieve a balance of medical efficiency and environmental satisfaction.

Infectious or Recovered? Optimizing the Infectious Disease Detection Process for Epidemic Control and Prevention Based on Social Media

Detecting the period of a disease is of great importance to building information management capacity in disease control and prevention. This paper aims to optimize the disease surveillance process by further identifying the infectious or recovered period of flu cases through social media. Specifically, this paper explores the potential of using public sentiment to detect flu periods at word level. At text level, we constructed a deep learning method to classify the flu period and improve the classification result with sentiment polarity. Three important findings are revealed. Firstly, bloggers in different periods express significantly different sentiments. Blogger sentiments in the recovered period are more positive than in the infectious period when measured by the interclass distance. Secondly, the optimized disease detection process can substantially improve the classification accuracy of flu periods from 0.876 to 0.926. Thirdly, our experimental results confirm that sentiment classification plays a crucial role in accuracy improvement. Precise identification of disease periods enhances the channels for the disease surveillance processes. Therefore, a disease outbreak can be predicted credibly when a larger population is monitored. The research method proposed in our work also provides decision making reference for proactive and effective epidemic control and prevention in real time.

A BIM-Based Value for Money Assessment in Public-Private Partnership: An Overall Review

Public-private partnerships (PPPs) have proliferated and adapted to public development in recent decades; within it, the value for money (VfM) assessment defines the feasibility of the project procurement model as one of the essential components of PPP. However, evaluating the VfM in PPPs remains problematic. Given concerns about PPP profitability, a more integrated VfM evaluation is urgently needed to manage multiple indicators along the project lifecycle. Building information management (BIM), popular in architecture, engineering, and construction, provides resources that could support the VfM to a great extent. This paper uses a review approach to identify the current issues that are affecting VfM assessments and suggests that BIM, functioning throughout the PPP lifecycle, could support decision-making in VfM processes in order to satisfy service targets.