Building inspection with automated code compliance checking

Inspecting existing buildings for conformity with current regulations is often difficult to carry out for people lacking expertise in code compliance checking. The present research aims at developing an automated approach for the diagnostic of existing buildings during inspection. The proposed methodology is that of an intelligent system combining current computer technologies such as expert systems, databases, and hypertext techniques. The expert system represents and reasons with specialist knowledge to diagnose problems with code compliance checking whereas the database and hypertext techniques are the database and hypertext techniques are efficient for handling cross references among distinct building subsystems and disciplinary viewpoints in data management systems. The research methodology has been implemented in a software prototype known as Health and Safety Expert System (HASES). The prototype system relies on knowledge and reasoning to interpret the requirements of Part 3 of the National Building Code of Canada. HASES aims at facilitating the inspection of existing buildings by simplifying the data collection and compliance checking processes, generating reports, and providing access to texts and relevant case studies on the fly, as an inspector walks around a building.