A Novel Machine Learning Approach for Classification at the Network Edge
TS-073225 —
In today's world, we are increasingly using low-cost devices with limited resources (often referred to as "edge devices") which are supported by connected high-performance servers. However, these edge devices often can't handle complex tasks such as classifying data. To make this possible, we need…
- College: College
of
Engineering
(COE)
- Inventors: Li, Chengzhang; Eryilmaz, Atilla; Ju, Peizhong; Shroff, Ness
- Licensing Officer: Giles, David
Robust Positioning and Navigation Using Low Earth Orbit Satellite Signals
TS-072827 — The Need
Current navigation systems, such as GNSS, face limitations in urban canyons, indoor environments, and areas with signal jamming or spoofing. The rapid proliferation of LEO satellite constellations presents an untapped opportunity for resilient, accurate positioning. However, leveraging thes…
- College: College
of
Engineering
(COE)
- Inventors: Kassas, Zak
- Licensing Officer: Ashouripashaki, Mandana
Vectorized Channel Estimation and SINR Optimization for Ultra-Wideband Communications
TS-070631 — The Need
Ultra-wideband communication systems, including mmWave and optical wireless networks, demand highly accurate and low-latency channel estimation to maintain throughput and reliability. Existing methods, such as hybrid correlation and least squares estimators, suffer from high computational c…
- College: College
of
Engineering
(COE)
- Inventors: Cai, Jian-Feng; Mao, Chongchang; Xian, Poline Y.; Xue, Ye; Zhang, Haiming
- Licensing Officer: Ashouripashaki, Mandana
Advanced LEO Satellite-Based Position, Navigation, and Timing Solutions
TS-069653 — Technology Bundle: T2025-053, T2025-055, T2025-056
The Need
Current global navigation satellite systems (GNSS) face significant challenges, including signal vulnerability to interference, limited coverage in urban and remote areas, and insufficient accuracy for high-precision applications. There is a critical need for more robust, accurate, and rel…
- College: College
of
Engineering
(COE)
- Inventors: Kassas, Zak; Kozhaya, Sharbel
- Licensing Officer: Ashouripashaki, Mandana
Sustainability-Aware Management of Autonomous Mobile Robot (AMR) Fleets
TS-068477 — The Need
Autonomous Mobile Robots (AMRs) are critical to modern, highly automated environments, operating 24/7 to optimize tasks, increase throughput, and meet demanding operational requirements. However, most task allocation and charging solutions focus solely on maximizing performance metrics like…
- College: College
of
Engineering
(COE)
- Inventors: Brocanelli, Marco
- Licensing Officer: Randhawa, Davinder
Color Correction System for Accurate Colorimetric Smartphone Measurements
TS-066957 — The Need
Colorimetric tests and remote image analysis are used in a wide range of industrial and medical applications. Digital image-based measurements made with smartphones are a promising platform to quantify colors at low cost, but suffer from inconsistency and errors caused by lens quality, sen…
- College: College
of
Engineering
(COE)
- Inventors: Dannemiller, Karen; Panescu, Jenny; Qin, Rongjun; Song, Shuang; Zhang, Guixiang
- Licensing Officer: Ashouripashaki, Mandana
System and Method of Securing Vehicle-Pavement Interaction (Tago)
TS-063169 —
Road safety is a paramount concern. Unpredictable road conditions, such as bumps and uneven surfaces, can pose significant risks to drivers. There is a pressing need for a technology that can sense and alert drivers about these road surface conditions in real-time, enhancing safety and improving t…
- College: College
of
Engineering
(COE)
- Inventors: Athreya, Kannan; Sun, Wei
- Licensing Officer: Randhawa, Davinder