Presented By O'Reilly and Cloudera
Make Data Work
December 1–3, 2015 • Singapore

Iot conference sessions

2:20pm–3:00pm Wednesday, 12/02/2015
Masaru Dobashi (NTT DATA Corporation), Yoshitaka Suzuki (IHI Corporation)
We are developing a platform to process massive sensor data obtained from social infrastructures and industrial machinery all over the world, in order to achieve advanced safety management. In this session, we'll talk about the capability of Spark to realize time-series data processing, the best practices of application development, and realistic lessons on operating Spark on YARN.
2:20pm–3:00pm Thursday, 12/03/2015
Fangjin Yang (Imply)
Organizations frequently rely on dedicated query layers, such as relational databases and key/value stores, for faster query latencies; but these technologies suffer many drawbacks for analytic use cases. In this session, we discuss examine using Druid to power applications designed to analyze sensor data, and why the architecture is well suited for different use cases in “smart cities”.
4:50pm–5:30pm Thursday, 12/03/2015
Majken Sander (TimeXtender), Joerg Blumtritt (Datarella)
Algorithms are what make things "smart." More or less arbitrary, subjective decisions are regularly built into our connected things, when we choose a certain method or set parameters. These underlying value judgments imposed on users are hardly present in the privacy discussion or business point of view. However, they may be more important than the more obvious data collection and security.
4:00pm–4:40pm Wednesday, 12/02/2015
Danielle Dean (Microsoft)
Predictive maintenance is a technique to predict when an in-service machine will fail so that maintenance can be planned in advance. This talk introduces the landscape and challenges of predictive maintenance applications in the industry. Through a real-world example, the talk also illustrates how to formulate a predictive maintenance problem with three machine learning models.
1:30pm–2:10pm Thursday, 12/03/2015
Markus Kirchberg (Deep Labs Pte. Ltd.)
In this talk, we will first take a look at current IoT standards, solutions, and common challenges; change management; and near real-time decision-making capabilities that are yet to be adequately addressed.