Viking Analytics and iioote, Gothenburg, Sweden, announced a new method for detecting black mold (Stachybotrys chartarum) in buildings using artificial intelligence (AI). The algorithm uses data collected by sensors to detect variations in temperature and humidity that indicate the risk of fungus growth, known for causing damage in construction materials such as fiberboard and drywall.
Humidity, temperature, and leakage sensors are installed in places where there is a high risk of water damage, where they constantly register and transmit measurements. The collected information is analyzed by an anomaly detection algorithm. When the risk levels for black mold rise, the interface triggers a notification.
The detection method is the result of a partnership between the companies that started in September 2019 to address the needs of water and sewage treatment companies and insurance companies to detect black mold earlier. Monitoring and detecting moisture before it can cause extensive damage is extremely important to construction companies, landlords, property owners, and insurance companies.
The use of AI saves time spent in manually evaluating data and allows professionals without a background in data science to analyze and make decisions.
Viking Analytics, founded in 2017, produces software for manufacturing, chemical, and process industries. iioote works with companies, organizations, and municipalities in implementing IoT.
Photo by Burdun Iliya.