SMILab Presents Results for Safer Wireless Sensor Networks

SMILab at UNM presents results on cyber security research and training for safer Wireless Sensor Networks, Structural Health Monitoring and Secure Digital Twins.

The New Mexico Consortium is supporting the exploration of cyber security in the context of Structural Health Monitoring and Advanced Wireless Sensor Networks. The project is part of a common collaboration between the University of New Mexico’s (UNM) Smart Management of Infrastructure Laboratory (SMILab) and the ongoing efforts on safer Structural Health Monitoring (SHM) using Wireless Sensor Networks (WSN).

This research addresses new concerns related to Cyber Physical Systems (CPS) with an emphasis on the areas of machine learning and cyber secured digital twins. The area of cybersecurity in SHM and WSN is the backbone of a partner project between SMILab and the Office of Naval Research (ONR) to educate and train Reserve Officer Training Corps (ROTC) students from all service branches in the principles of CPS and Cybersecurity. The importance of Cybersecurity goes beyond algorithms and simulations when it involves real structures, events, and communities. The ROTC training is a project co-lead by Dr. Moreu from the Department of Civil, Construction and Environmental Engineering and Dr. Sorrentino from the Department of Mechanical Engineering, which trained cadets through COVID since Spring 2020 to date.

The group’s approach involves teaching how to fabricate and protect smart sensors, particularly SMILab’s Low-cost Efficient Wireless Intelligent Sensors (LEWIS). These sensors are a Cyber Physical system and have multiple modular capabilities in which real time data can be collected to inform important decisions, such as increasing environmental efforts in a community or closing off a bridge that may no longer be secure, protection of roads from falling rocks, or generating digital twins in the field with advanced sensing.  With the sensor’s data collection capabilities, there comes a concern about the trustworthiness of the data sent from the sensor. This group aims to ease that concern by cyber securing their systems which allows the Cyber Security principles they learn to be put into practice. Collectively, the group’s sensors are not only used to educate but as a tool for smart cities.

The students from SMILab presented their various research projects on September 26, 2021 at the Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering & Technology (MMLDT-CSET) Conference in San Diego, California. The conference was held to bring the vast and various communities researching mechanistic machine learning and digital twins together to apply these concepts to extensive problems both in academia and everyday life. All topics were presented in the special session chaired by Dr. Moreu and Dr. Mascarenas (Los Alamos National Laboratory) entitled “Machine Learning and Hybrid Simulation for Civil Infrastructures.” Below are the pictures of the students who presented their work towards safe, intelligent, and reliable “Digital Twins”: Joshua Murillo, Roya Nasimi, and Xinxing Yuan.

The ongoing ONR project is addressing growing concerns about cyberwarfare, with the intention of preparing a more cyber prepared force to deal with emerging cyber threats. This program has been running for 2 years and initially began with 3 students. Graduate student United States Marine Corps 2nd Lieutenant Joshua Murillo currently works with 10 multidisciplinary students both civilian and ROTC, from all varying fields of study. The fields include: Global and National Security, History, Economics, Computer Science, and Mechanical Engineering.  More recent activities of the group include recruitment, on September 2, 2021 both 2nd Lieutenant Murillo and Dr. Moreu briefed the UNM Naval ROTC (NROTC) unit on this project and intend to teach a sensor class to the entire NROTC unit in the near future.

Article by Joshua Murillo and Fernando Moreu. Photo at top of article of LEWIS 5.1 sensor ready for deployment in Ohkay Owingeh.