Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
School of Computer Science & Software Engineering CITS4419 Mobile and Wireless Computing Case Study: Water Sensitive Cities Week 8 Tuesday 16 September 2014 In this lecture we study data mining and analysis techniques through two case studies: data mining for smart water meter data and biomedical time series analysis. The topics covered are: introduction to data mining; patterns and behavior extraction from smart water meter data; benefits of data mining to analyze smart water meter data; biomedical time series representation and characterization; biomedical time series classification and clustering. Questions: Listen to the lecture and answer the following questions. What are the benefits of smart water metering? What are the benefits of data mining for smart water meter data analysis? What are the challenges of data mining for smart water meter data analysis? In your opinion, what kinds of information can be extracted by data mining algorithms from smart water meter data? Besides raw water consumption data, what kinds of other context information (e.g., weather) may be helpful for us to mine more useful information from smart water meter data? From a point view of computer science, what are the challenges to automatically analyze large amount of data (big data), e.g., smart water metering data, biomedical time series and so on?