MUMBAI, India, July 7 -- Intellectual Property India has published a patent application (202641078368 A) filed by Cmr Engineering College, Kandlakoyav, Medchal Road, Hyderabad, Medchal Malkajgiri, Telangana-, India. on June 25, 2026, for Ai-Powered Smart Urban Planning And Resource Allocation Platform.
Inventors include Dr. Madhavi Pingili, Professor, Computer Science And Engineering Aiml, Cmr Engineering College; Mrs. T Virajitha, Assistant Professor, Computer Science And Engineering Data Science, Cmr Engineering College, Kandlakoyav, Hyderabad; Ms. G. S. Sravanthi, Assistant Professor, Computer Science; Dr. V. Mani Sharma, Associate Professor, Computer; Mrs. Usharani Gude, Assistant Professor, Computer; Ms. Pakeeza Fatma, Assistant Professor, Computer Science And Engineering, Cmr Engineering College, Kandlakoyav, Hyderabad; and Dr. Suman Mishra, Professor, Electronics And Communication Engineering, Cmr Engineering College, Kandlakoyav, Hyderabad.
The application for the patent was published on July 03, 2026, under issue no. 27/2026.
Abstract: The present invention discloses an AI-Powered Smart Urban Planning and Resource Allocation Platform for intelligent city management and sustainable urban development. The platform integrates Artificial Intelligence (AI), Internet of Things (IoT), Geographic Information Systems (GIS), cloud computing, and machine learning technologies to monitor urban environments and optimize resource allocation. Urban data are collected from IoT sensors, surveillance systems, smart meters, transportation networks, environmental monitoring stations, and citizen service platforms. The collected data undergo preprocessing operations including cleaning, normalization, feature extraction, and multi-source data fusion. Machine learning algorithms including Random Forest, XGBoost, Support Vector Machine (SVM), Deep Neural Networks (DNN), and Long Short-Term Memory (LSTM) networks are employed to predict traffic demand, energy consumption, water usage, population growth, and infrastructure utilization. Based on predictive analytics, the system dynamically allocates urban resources such as transportation services, energy distribution, water supply, waste management, and emergency response facilities. GIS-based visualization provides real-time situational awareness through maps, dashboards, and urban analytics reports. The platform supports cloud and edge computing architectures for scalable deployment and low-latency processing in smart city environments. The proposed invention improves operational efficiency, reduces resource wastage, enhances public services, and promotes sustainable urban growth. The system is applicable to municipal corporations, smart city infrastructures, urban development authorities, and government agencies seeking intelligent and data-driven urban planning solutions.
Disclaimer: Curated by HT Syndication.
