Research Terms
This multi-access edge computing system connects and coordinates signals from multiple smart devices to provide real-time monitoring on remote construction work sites. The U.S. construction industry, valued at $2.1 trillion, is one of the largest markets in the nation. However, the industry is one of the least productive, operating in a high-risk environment. A major barrier construction projects face is the low access to high-speed internet and computing, making processing capabilities finite. Working in a dynamic and rapidly changing environment, hazard assessment is nearly impossible, and site monitoring and real-time communication are severely limited. Currently, the industry is heavily reliant on manual, time-consuming, and labor-intensive processes. But the construction industry is an environment ripe for automation. Emerging information and communication technologies offer the opportunity to address these industry challenges and beyond.
Researchers at the University of Florida have developed a multi-access edge computing system to manage signals to and from various heterogeneous sensors, software, and technology using the Internet of Things (IoT) architecture. This system, IoT-ACRES (IoT- Applied Construction Research and Education Services) uses machine learning to facilitate learning from new data to update upstream models. This enables safety risk analysis, site monitoring, and real-time updates of any aspect of a job site. It joins the physical and virtual worlds together, bringing computation and data to the source.
Multi-access edge computing system using the Internet of Things (IoT) incorporates various heterogeneous sensors, technology, software, and AI to provide real-time construction site monitoring and feedback
This multi-access edge computing system utilizes the Internet of Things (IoT) to incorporate a multitude of heterogeneous solutions and provide construction site tracking. It comprises sensors, edge computing, cloud computing, and local computing systems. The sensors collect data from the site and transmit it to the local computing system, which in turn processes it and transmits the results to the edge computing system. The edge computing system functions as a middleman, processing data at an edge location of a local network at the construction site before sending the information to the cloud computing systems. The cloud computing system uses cloud servers and machine learning models to collect and compile the data processed by edge computing systems. The integration of data from localization systems with other internet-enabled sources can provide valuable information on real-time safety risks and system optimization.
This hardware-based security gateway for Internet of Things (IoT) and wireless sensor networks protects data by shifting security processing from software to a secure module, enabling faster, lower-latency communication and thermal performance while strengthening security. Globally, more than 29 billion devices are connected to the internet, many of them operating as resource-constrained sensors and edge nodes. These heterogeneous devices often rely on software-only security, which increases processor load, power use, and delay and exposes keys to malware and physical tampering. As deployments expand to dynamic, infrastructure-intensive environments such as industrial and remote sites, gateways must secure increasingly large data streams between device networks, edge systems, and cloud services. However, traditional software-only gateways fail to secure communication without degrading performance.
Researchers at the University of Florida developed a hardware-based security gateway for IoT and wireless sensor networks that integrates a dedicated hardware security module (HSM) to isolate cryptographic operations from the main processor. By implementing hardware-based encryption, key storage, and tamper detection, the system improves performance while enhancing security across heterogeneous IoT deployments. This security gateway has been validated in infrastructure-intensive environments such as construction sites and supports broader industrial and edge computing applications.
Secure, low-latency edge gateway that protects IoT sensor data and control traffic for construction sites and other industrial edge computing environments
This hardware-based security system for IoT and wireless sensor networks secures data by integrating a hardware security module (HSM) into an IoT gateway that connects diverse devices to edge and cloud networks. The gateway software manages device communication, while the HSM performs all cryptographic operations, including key generation, secure storage, encryption, decryption, and digital signing, independent of the main processor. The gateway routes incoming device data through the HSM, which enforces encryption and authentication before transmission beyond the local network. The security module generates and stores cryptographic keys entirely within hardware, preventing exposure to system memory or application software. The HSM also monitors physical integrity, enabling detection of tampering or unauthorized access.
