Wireless infrastructure is steadily evolving into wireless access for all humans and most devices, from 5G to Internet-of-Things. This widespread access creates the expectation of custom and adaptive services from the personal network to the backbone network. In addition, challenges of scale and interoperability exist across networks, applications and services, both requiring an effective wireless network management infrastructure. At the same time, there has been a rising imperative to capitalize on the current technological advancements to address to the most pressing issues surrounding construction and the built environment to increase health and safety; productivity; and sustainability. This Elements project combines the areas of computer science, electrical engineering, and construction and building to develop a robust cyberinfrastructure (CI) service for construction research, as well as applications that utilize state-of-the-art emerging technologies and software to address the current challenges faced by the construction industry. The major contribution of the project is the development of the IoT-ACRES (IoT-Applied Construction Research and Education Services) system, a central, interoperable framework hub that can incorporate a variety of heterogeneous sensors, technology, software, managed by a software-defined network infrastructure and optimized by machine learning and artificial intelligence techniques. The prototype system will help to augment the works and/or safety manager's ability to detect hazards and subsequently improve safety performance in construction, which is one of the greatest challenges faced by the construction industry. In addition, the framework can be used to increase autonomy in applications that require simultaneous tracking of multiple entities (people, vehicles, equipment, etc.), detecting multiple objects of interests, analyzing real-time biometric data, and making autonomous decisions. Results will be disseminated to industry and research communities through publications and presentations at workshops, training courses and online professional certification programs. The project will also be used as a research, education, and training tool to (1) mentor and teach K-12 students about STEM, and (2) to develop and enhance courses to educate the current and next generations of students, users, and workers, on the latest technology and the latest approaches to cyber security techniques.
This project develops a robust cyberinfrastructure (CI) system and service for construction research and applications to address the current challenges faced in the construction industry. The outcomes and services that this proposal aims to provide are 1) a distributed SDN-managed and AI-assisted IoT-based system that can be adapted and extended based on needs of the research and application; 2) identification of the data and data security requirements needed to address the challenges in the construction industry and potential technologies that can provide those data; 3) evaluation of reliable real-time multi-sensor fusion techniques for ruggedness, usability, and limitations of IoT-based components deployed in the dynamic construction environments; 4) robust prototype system for real-time safety monitoring based on the IoT system framework; and 5) recommendations of potential configurations of the system with the appropriate technology and sensors to meet the needs of the application. The empirical data resulting will be delivered through yearly NSF reports on the progress and findings, journal publications of the intellectual merit and scientific findings, and conference proceedings discussing the broader impacts and future research objectives. The framework of the hardware and software, including an instructional manual will also be published. The software will be made available through request via a project website, open source posts, and conference and workshop dissemination. The project will explore the use of various delivery mechanisms, such as NSF's eXtreme Science and Engineering Discovery Environment (XSEDE). The IoT-ACRES will utilize IBM IoT Continuous Engineering and Cloud Computing Servers Cloud (e.g. Amazon AWS) for the data analysis and performance metrics. This novel convergence research project will ultimately advance the development of sustainable CI communities and stewardships of sustainable CI services that can enhance productivity and accelerate innovation in science and engineering. This work will advance practices of safety controls by developing a tool for safety monitoring on construction sites, presented to safety managers with interfaces that visualize, and report real-time safety hazards. Significantly, it will address fundamental research challenges in computer vision and construction management: improving context-based object recognition and tracking; and formalizing rules for integrating visual, textual, biometric data to proactively recognize safety hazards.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
