Many research studies have focused on fire evacuation planning. However, because of the uncertainties in fire development, there is no perfect solution. This research proposes a fire evacuation management framework which takes advantage of an information-rich building information modeling (BIM) model and a Bluetooth low energy (BLE)-based indoor real-time location system (RTLS) to dynamically push personalized evacuation route recommendations and turn-by-turn guidance to the smartphone of a building occupant. The risk score (RS) for each possible route is evaluated as a weighted summation of risk level index values of all risk factors for all segments along the route, and the route with the lowest RS is recommended to the evacuee. The system will automatically re-evaluate all routes every 2 s based on the most updated information, and the evacuee will be notified if a new and safer route becomes available. A case study with two testing scenarios was conducted for a commercial office building in Tianjin, China, in order to verify this framework.

While many countries have developed green building rating systems (GBRSs) to promote the concept of green buildings, it is difficult for designers to achieve better sustainability in the design process when using the real-time green building rating score as a reference. This paper proposes an intelligent green building rating (iGBR) framework supported by a semantic and social approach to realize real-time rating in building design. The framework features four components: (1) An ontology that is used to encapsulate the knowledge of green building rating, (2) score calculation rules that are encoded in Semantic Web Rule Language (SWRL), (3) Autodesk Forge, which is employed as a building information modeling (BIM)–based design platform to synchronize design models from different professions in the cloud, and (4) a group chat tool to connect all project participants in a social communication environment to effectively exchange data/information required for score calculation. A prototype iGBR system is developed based on the Evaluation Standard for Green Building of China (ESGBC) to verify the framework, so that a total of 95 articles can be assessed automatically in the real-time approach.

Commercial and public buildings are more vulnerable to fires because of their complex use functions, large number of centralized occupants, and the dynamic nature of the use of space. Due to the large number of these types of buildings and the limited availability of manpower, annual fire inspections cannot ensure the continuous compliance of fire codes. A crowdsourcing application, iInspect, is proposed in this paper to harvest collective intelligence in order to conduct mass inspection tasks. This approach is supported by building information modeling (BIM) based virtual reality (VR) and an indoor real-time localization system. Based on the International Fire Code and 27 fire inspection checklists compiled by various local authorities, a generic list of inspection items suitable for iInspect is proposed, along with a reputation-based monetary incentive model. A prototype of iInspect was created for Android mobile phones, and a case study was performed in an office building in Tianjin, China, for verification of this crowdsourcing inspection approach.