A proposed method for generating high resolution current and future climate data for Passivhaus design

The sensitivity of low energy and passive solar buildings to their climatic context creates a requirement for accurate local climate data. This situation takes on increasing importance in the context of modelling Passivhaus buildings where the absence of conventional oversized heating and cooling systems implies a greater reliance upon fabric and system optimisation. Conversely, future climatic changes may also pose serious implications for super insulated buildings with inadequate solar shading. Currently, many widely used building performance simulation (BPS) tools still rely on very limited sources of climate data. The following research examines the need for regional and, in some cases, micro-regional climatic data when designing ultra-low energy Passivhaus buildings in the UK. The paper proposes a new methodology for generating this data in PHPP format. The data generated is compared to alternative sources, and the implications discussed in the context of three case studies examining a certified Passivhaus dwelling in a mountainous region of Wales as well as two locations, in close proximity, within London. If correctly implemented the use of such data should provide a more robust basis for future cost and performance optimisation in low energy and passive building design

An IT-based approach to managing the construction brief

The present paper gives a comprehensive overview of the CoBrITe1 project. The aims and objectives of the project are described, followed by a detailed definition and characterization of the briefing process. An overview is then given of the current technology used by the CoBrITe industrial partners to support briefing. The paper also introduces five key areas that can promote effective briefing: communication, information capture, information referencing, information representation, and change management. Finally, the CoBrITe system demonstrator is presented

IT tools and support for improved briefing

The present paper gives a comprehensive overview of the CoBrITe1 project. First, the aims and objectives of the project are described, followed by a detailed definition and characterization of the briefing process. Then, an overview of the current technology implementations of the CoBrITe industrial partners is given. The paper also introduces five key areas that can promote effective briefing: Communication, Information capture, Information referencing, Information representation, and change management. Finally, the CoBrITe system architecture is presented. The project is ongoing and supported by the Link / IDAC program

[Comment] Give UK science the overhaul it urgently needs

As the United Kingdom installs its next government, most of the problems it must tackle — from environmental to medical and social issues — are underpinned by science research and policy. Nature spoke to five researchers about their concerns and what actions they think the government should take.</p

AI-big data analytics for building automation and management systems: a survey, actual challenges and future perspectives

In theory, building automation and management systems (BAMSs) can provide all the components and functionalities required for analyzing and operating buildings. However, in reality, these systems can only ensure the control of heating ventilation and air conditioning system systems. Therefore, many other tasks are left to the operator, e.g. evaluating buildings’ performance, detecting abnormal energy consumption, identifying the changes needed to improve efficiency, ensuring the security and privacy of end-users, etc. To that end, there has been a movement for developing artificial intelligence (AI) big data analytic tools as they offer various new and tailor-made solutions that are incredibly appropriate for practical buildings’ management. Typically, they can help the operator in (i) analyzing the tons of connected equipment data; and; (ii) making intelligent, efficient, and on-time decisions to improve the buildings’ performance. This paper presents a comprehensive systematic survey on using AI-big data analytics in BAMSs. It covers various AI-based tasks, e.g. load forecasting, water management, indoor environmental quality monitoring, occupancy detection, etc. The first part of this paper adopts a well-designed taxonomy to overview existing frameworks. A comprehensive review is conducted about different aspects, including the learning process, building environment, computing platforms, and application scenario. Moving on, a critical discussion is performed to identify current challenges. The second part aims at providing the reader with insights into the real-world application of AI-big data analytics. Thus, three case studies that demonstrate the use of AI-big data analytics in BAMSs are presented, focusing on energy anomaly detection in residential and office buildings and energy and performance optimization in sports facilities. Lastly, future directions and valuable recommendations are identified to improve the performance and reliability of BAMSs in intelligent buildings.Other Information Published in: Artificial Intelligence Review License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s10462-022-10286-2</p