SIE558 Real-time sensor data streams final projects

Here are some impressions from the final project presentations of the SIE 558 Real-time Sensor Data Stream course. — The projects included

  • An Arduinos and raspberry pi-based sensor network to send  automatic alerts when the dog would open the fridge and check the trash can
  • data analysis in the Damariscotto river and
  • data analysis of fertilizer run-off in the Mississippi delta
  • an Arduino-based  heart rate monitoring system, and
  • a Arduino-based house plant monitoring system

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Congratulations, Xueying!

Today, Xueying Gu, successfully presented his MS project. Congratulations!Screen Shot 2015-12-15 at 12.11.26 PM

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Xueying Gu’s MS project presentation

Master Project Presentation — Dec 15 2015, 11am SIE Library

AN ONTOLOGY-BASED APPROACH FOR ACTIVITY RECOGNITION FROM SENSORS IN OFFICES

Xueying Gu

Project Advisor: Dr. Silvia Nittel
Co-Advisor: Dr. Torsten Hahmann

Understanding the behavior of people in a building can be useful to save energy in buildings and improve efficiency of employees. To study the behavior of people in office buildings, sensors can be used to collect raw data about people’s presence in rooms and their movement through buildings. However, to understand higher-level behavioral patterns, we first developed an application ontology, written in Common Logic, that describes this information of interest at a higher level of abstraction. For example, which characteristics constitute a meeting? How are they related to movement data? Following, we translate the defined ontological concepts into MySQL scripts and Java algorithms to ‘mine’ the low-level sensor data stored in a relational database system. With the programs, we can retrieve some important information about offices such as: how frequently are offices and shares spaces utilized? How many meetings take place on average during a week? A number of use cases demonstrate the capabilities of the system.

Does this sound familiar?

The stages of the creative process. Encountered in every paper, or thesis. Does this sounds familiar?

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Our latest grant in the UMaine News

For more information, check this link https://umaine.edu/news/blog/2015/09/25/umaine-researchers-receive-nsf-award-to-improve-sensor-data-collection-analysis/

GSN Lab shows demos at the UMaine Open University Day

Today, UMaine celebrated the research at UMaine with an Open University Day during the 150 year anniversary Homecoming celebrations, open to the public. We demo-ed the live soil moisture sensor network from the blueberry barrens as well as a field based temperature network, and had a good turnout of visitors. Thank you everyone for participating!

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New publication “Emerging Technological Trends likely to Affect GIScience in the Next 20 Years”

In July 2015, Silvia Nittel, Lars Bodum, Keith Clarke, Michael Gould, Paulo Raposo, Jayant Sharma, and Maria Vasardani served as members of the “Emerging Technological Trends likely to Affect GIScience in the Next 20 Years” panel, which was part of the Twenty Year Anniversary of the International Early-Career Scholars Summer Institutes in Geographic Information Vespucci Institute in Bar Harbor, Maine in 2015. In this book chapter, the panelists summarize their findings about major technological developments that potentially will required novel research in GIScience.

Find the paper here.

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