https://joaocarlos.github.io/Hugo-academia/tags/machine-learning/Recent content in Machine Learning on Dr. Jane SmithHugoenFri, 15 Sep 2023 00:00:00 +0000https://joaocarlos.github.io/Hugo-academia/books/ml-smart-cities/Fri, 15 Sep 2023 00:00:00 +0000https://joaocarlos.github.io/Hugo-academia/books/ml-smart-cities/Description This comprehensive textbook provides a thorough introduction to machine learning techniques and their applications in smart city environments. Written for graduate students and practitioners, the book covers both theoretical foundations and practical implementations. Table of Contents Introduction to Smart Cities Data Collection and Sensor Networks Machine Learning Fundamentals Deep Learning for Urban Data Reinforcement Learning for Control Systems Privacy and Security Considerations Case Studies and Applications Future Directions Reviews “An essential resource for anyone working at the intersection of AI and urban computing.https://joaocarlos.github.io/Hugo-academia/projects/ai-for-traffic-optimization/Mon, 01 Jan 0001 00:00:00 +0000https://joaocarlos.github.io/Hugo-academia/projects/ai-for-traffic-optimization/Project Overview This project developed novel machine learning algorithms for real-time traffic signal optimization. By analyzing historical traffic patterns and real-time sensor data, our system dynamically adjusts signal timing to minimize congestion and reduce emissions. Key Achievements Reduced average commute times by 12% in pilot districts Decreased vehicle emissions by 8% through improved traffic flow Deployed system in 3 cities (San Francisco, Oakland, San Jose) Technology licensed to commercial traffic management companies Publications Smith et al.