Annually, the United States spends over $42 billion on leak and moisture related energy costs; the leaks are hard to find, and the current processes to locate them are intrusive, expensive, and a hazard to worker safety.
Alum Bilal Sher (‘22) is working to address that. His start-up, Building Diagnostic Robotics, as the name implies, leverages robotic technology and artificial intelligence to locate and identify damaging leaks and to provide a comprehensive evaluation of a building's physical condition, performance, and overall health.
The company had its genesis when Sher was a master’s student in Tandon’s AI4CE lab under the direction of Professor Chen Feng. His work there resulted in a prototype he and his team called EASEEBot, a drone capable of climbing up a building’s outer facade and flying over it to deploy digital and thermal cameras, thereby allowing it to identify air leaks, defects, and intrusions.
EASEEBot, which could work in confined spaces, allowing workers to stay out of hazardous areas, garnered a string of high-profile laurels, including a Civic Innovation Challenge award from the National Science Foundation (NSF) and the Department of Homeland Security, inclusion in the NYC Smart City Testbed Program, funding from NSF I-Corp, and an invitation to participate in NYU’s Tech Venture Accelerator.
Sher — who earned a B.S. in Civil Engineering from the University of Calgary and worked analyzing disaster-damaged structures in the U.S. Virgin Islands before arriving in Brooklyn for graduate studies–finds it gratifying to have developed a cost-effective, labor-efficient, non-invasive, and scalable way to contribute to the planet’s health and sustainability. “I like to see my work leave a lasting impression and I find it very satisfying to know that buildings and sites I have worked on will be used by and benefit many people,” he says.
