AI‑Driven Network Optimization Using Predictive Location Intelligence (Artificial Intelligence Automation to Improve Network Quality Based on Predicted Locations, Tech ID: 23‑010)
Technology Overview: This technology applies artificial intelligence to predict user locations and proactively optimize network resources. By anticipating movement patterns and connectivity demand, the system dynamically adjusts network parameters to improve quality‑of‑service, reduce latency, and enhance user experience. The approach is particularly effective in dense urban and mobile environments.
Industry Pain Point: Network optimization is reactive, leading to congestion and degraded performance during demand spikes.
NJIT Solution: AI‑based prediction enables proactive network optimization, improving reliability and efficiency.
Key Features & Advantages
- AI‑driven location prediction
- Proactive quality‑of‑service optimization
- Reduced latency and dropped connections
- Scalable across cellular and Wi‑Fi networks
Development Stage: TRL 4–5 – System‑level validation completed.
Target Markets
- Mobile network operators
- Smart cities infrastructure
- Wireless network management platforms
Market Opportunity
- Global telecom software market (2026): ~$95B
- CAGR: ~7–8%
- Projected market size (2035): ~$175–190B
Commercial & IP Details
Inventors: Cristian Borcea, Manoop Talasila, Yi Chen, Xiaopeng Jiang, Shuai Zhao, Anwar Aftab, Wen‑Ling Hsu, Guy Jacobson, Rittwik Jana