Using the Internet of Things (IoT) embedded in the built environment as the infrastructure for Digital Twin
Project 1: Internet of Things Enabled Data Acquisition Framework for Smart Building Applications
The team developed an IoT-enabled data acquisition framework for smart building applications. This framework integrates low-cost computers, sensors, software agents, and existing Wi-Fi networks to create a central facility database. It enables the collection and integration of building data for smart city applications. We built a prototype system and conducted a case study on a university campus, demonstrating the framework’s effectiveness in creating a scalable, cost-effective, and portable building data acquisition system, contributing to smart building innovations.
Project Team: Dr. Ray Gao, Dr. Pardis Pishdad‐Bozorgi, Dr. Dennis R Shelden, and Dr. Shu Tang.
Project 2: A cost-effective, scalable, and portable IoT data infrastructure for indoor environment sensing
We developed a cost-effective, scalable, and portable indoor environment data collection system named Building Data Lite (BDL). Utilizing Raspberry Pi computers and various sensors, BDL gathers data on temperature, humidity, light, motion, sound, vibration, and gases. It features a distributed sensing network and a centralized server with a web-based interface for data access. The system was evaluated through a case study in an affordable housing community, demonstrating its functionality, affordability, scalability, portability, and ability to collect diverse types of indoor environment data.
Project Team: Sheik Anik, Dr. Ray Gao, Dr. Na Meng, Dr. Philip R. Agee, and Dr. Andrew P. McCoy.
Ray Gao's Cabinet of Curiosities 