AscHS Artificial Intelligence Projects

Archibus Solution Center – Hosting Services (AscHS), the leading provider of Archibus Cloud Solutions and the BRUCE Platform, announces a major development initiative with the introduction of two projects for the execution of an Artificial Intelligence strategy.

It is widely held that Artificial Intelligence can enhance many software solutions that are designed to manage real estate, property and facilities within the built environment. The key to this enhancing is the availability of verified data, so improving data onboarding and acquisition is an important step on the road to AI helping to reduce costs, helping managers make better decisions and ultimately improving building performance and the use of resources.

The Team as AscHS believes firmly that data is a fundamental building block of the process. Of course one challenge is the sheer variety of data sources and uses, whether traditional IWMS and CAFM data, sensor data in the internet of things or logs created from the tasks performed by building occupants.

Data Management

Data Management is a sensitive topic. Accordingly, AHS will be taking advantage of PPA (Privacy Preserving Analytics) Technology already embedded in BRUCE Platform that allow data to be analyzed while protecting the privacy of sources individuals. Offering accurate but secured benchmarking and data anlytics.

The objective is to take user-facing products to market within the calendar year.

Making informed decisions in the face of reduced budgets and resources is a major challenge in the built environment. Some of the outputs expected by the team enhance functions that already exist in traditional software. The ASC-HS Team will be targeting the following areas amongst many others:

• The use of AI to deliver validated data to give real insights to managers and enhance their decision making. They need to make informed decisions based on a full picture.
• The use of AI to improve the data for Environmental, Social, and Governance programs, focusing on sensor and meterage data. A key target here is energy efficiency.
• The use of AI to analyze maintenance history and asset performance data. Maintenance becomes a predictive activity, reducing costs and risk.
• The use of AI to enhance a traditional CAFM task – Space Optimization, analyzing real utilization and usage trends.

The Team believes that the output from these projects will benefit end user clients and business partners alike. Be ready for a series of news articles as we track the progress of these exciting developments.