Big Data Analytics for Smart City Infrastructure - F23

Timeline
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September 30, 2023Experience start
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December 19, 2023Experience end
Experience scope
Categories
Information technology Data analysis Operations Project managementSkills
machine learning data analysis sustainability rapidminer infrastructure engineeringStudent-consultants will analyze city data sets (normally available through open city portals, etc.) through state-of-the-art Machine Learning and Data Mining technologies, to: identify trends, and/or create predictive models. Their models are used to create solutions for infrastructure sectors (transportation, building, energy, urban water/drainage, etc.) which can be deployed using digitalization in smart cities.
Learners
The student will deliver the following:
- A 10 - 15 page report, explaining their problem statement and objectives, the methods they followed, The model they developed, and Their results;
- A 10-15 minute presentation
- The model(s) developed (in form of RapidMiner processes), as well as the pre-processed data they used
Project timeline
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September 30, 2023Experience start
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December 19, 2023Experience end
Project Examples
Requirements
Student-consultants will analyze urban data sets using data mining and machine learning technologies to improve city efficiency, sustainability and resilience.
Some past project examples include:
- Road Condition Assessment through Data Mining
- Real Estate Price Forecast through Data Mining
- Predictions for Available Parking Spots in Various North American Cities
- Analysis of Road Safety and Road Accidents
- Improving Building Thermal Comfort and Energy Performance using Machine Learning
- Analysis and Prediction of Energy Consumption Behavior at Building, District and City Level
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
Timeline
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September 30, 2023Experience start
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December 19, 2023Experience end