SIE559: Geosensor networking

Gearing up to the final project in SIE559: Geosensor networks — building a mesh network with Arduino Unos, Xbee radios, sensing end nodes, and an actuating Christmas tree light.




Simulating the 2018 Montecito Mudslide

As part of a research paper on real-time volunteer streams we used the 2018 Montecito Mudslide as our driving scenario this summer. Mike Cressey, a grad student in the SIE program, did most of the work of modeling the mudslide using the RAMMS software from Switzerland (under the supervision of Dr. Melissa Landon, Department of Civil Engineering). There were actually 4 different mudslides, and we modeled the Montecito Creek one.

Mike summarized the work and shows the animation in the following video:

Transactions of GIS Journal article on Real-time Streaming IDW published

Our article “Real- time inverse distance weighting interpolation for streaming sensor data” (Q. Liang, S. Nittel, J.C. Whittier, and Sytze De Bruin) has been published in Transactions of GIS. It is available as pre-print online (link). (TGIS2018_liang_nittel)


With advances in technology and an increasing variety of inexpensive geosensors, environmental monitoring has become increasingly sensor-dense and real-time. Using sensor data streams enables real-time applications such as environmental hazard detection, or earthquake, wildfire or radiation monitoring.
In-depth analysis of such spatial fields is often based on a continuous representation. With very large numbers of concurrent observation streams, novel algorithms are necessary that integrate streams into rasters or other continuous representations continuously in real-time.
In this paper, we present an approach leveraging data stream engines (DSEs) to achieve scalable, high-throughput Inverse Distance Weighting (IDW). In detail, we designed and implemented a novel stream query operator framework that extends general-purpose DSEs. The proposed framework includes a two-panel, spatio-temporal grid based index and several algorithms, namely the Shell and k-Shell algorithms, to estimate individual grid cell efficiently and adaptively for different sampling scenarios. For our performance experiments, we generated several different spatio-temporal stream data sets based on the radiation deposits in the Fukushima region after the nuclear accident in 2011 in Japan. Our results showed that the k-Shell algorithm of the proposed framework produces a raster based on 250K observations streams in under 0.5 seconds using a state of the art workstation.

J.C. Whittier graduating with a PhD

Yesterday, he submitted the final version of his PhD thesis to the grad school, and now is ready for new adventures. Time for some congratulatory beers with Qinghan Liang and Iranga Subasinghe at the Orono Brewing Company.


CS Senior Katelyn Manzo CLAS Outstanding Graduating Student

Katelyn (Katie) Manzo has been a member of the Geosensor Networks lab since August 2015, when she participated in a summer course in programming Arduinos. After doing exceptionally well in the required first year CS courses, she still was on the verge of dropping the major due to the mostly abstract content and question if it would be a right fight. Arduinos, on the other hand, were practical, hands on, and  fun. She understood all concepts in lightening speed, and made the perfect ‘hershey kisses’ right off the bat when sautering  the radio boards. A natural!


Katie practice soldering

She started to work as a MLA (Maine Learning Assistant) for COS250 in Fall 2016, and started with Dr. Nittel in the summer of 2016 as an undergraduate research assistant. She helped develop the course material for COS120: Computing that Matters, especially the Arduino and Database section, and made several instructional videos for the course.

In Fall 2016, she was a founding member of the ACM-W student group at UMaine, and became the group’s Vice President. The group has been very active organizing events for women in computing at UMaine and reached out to high school and middle school students. In 2017, Katie became the ACM-W president, and organized weekly meeting, programming meets and parties on top of her regular course load.

Since Spring 2016, Katie has participated in a project with Dr. Nittel, her advisor and mentor, and Dr. Sharon Klein, an Economics professor for Sustainable Energy. She familiarized herself with a recently developed website that collects data about US Community Renewable Energy Projects ( Supported via a Margaret Chase Smith Public Affairs Scholarship Katie added a social media component to the original website. The social media component includes user profiles and user discussion forums with regard to user-specific questions around community renewable energy. She has presented her research and work at the Center for Undergraduate Research’s Student Research Symposium in April 2018.

Katie is one of two women left in her graduating class; this is why she feels strongly about supporting women in computing, and the exposure of computing to middle school and high school girls are very important to her. This is also something that she hopes to carry through to the workplace when she graduates.

Katie topped it all of with being the College of Liberal Arts and Sciences Outstanding Graduating Student in 2018.  Congratulations, Katie! Very well done, we are very proud of you!

Here is an interview with Katie.


Katie Manzo CLAS Outstanding Graduating Senior, 2018

Katie with family

Katie with John and Family


Katie carrying the CLAS flag at Commencement


Katie and other CS students at Commencement

J.C. Whittier successfully defends PhD thesis

On April 27 2018, J.C. Whittier successfully defended his Phd thesis titled “Towards an efficient, scalable stream query operator framework for computing continuous fields”. His work has focused on developing a stream operator framework for spatio-temporal inverse distance weighting interpolation of massive sensor data streams. The stream query operator framework achieves a through-out of 100K tuples/sec, on a state of the art workstation. Furthermore, he developed a second stream operator framework that efficiently evaluates value predicates over continuous fields in real-time. Congratulation, J.C.!


4 graduate assistantships available (Fall 2018)

We have 4 graduate teaching assistantships available starting Fall 2018. If you are interested in getting a  PhD in real-time GIS, real-time sensor data streaming, geosensor networks, and social sensing, please apply!


The University of Maine, School of Computing and Information Science is seeking students interested in pursuing advanced degrees in spatial informatics and/or computer science. The school offers MS degrees in Spatial Information Science and Engineering, Spatial Informatics, Information Systems and Computer Science as well as PhDs in Computer Science and Spatial Information Science and Engineering.

Funding for several general graduate research assistantships and teaching assistantships is available from the School starting in September 2018.

Faculty research interests cover a range of topics in geographic information science, data science, and computer science that include: human computer interaction, real-time sensor data streaming, geosensor networks, ontologies and semantic modeling, spatial databases, information policy, spatial and temporal reasoning, and context modeling, among others. The school seeks students with research interests that align with the above research topics. Funding is available through graduate teaching and research assistantships.

Interested applicants should have prior experience or an undergraduate degree in computer science, geographic information science or a closely related degree. On line applications can be accessed through the University of Maine Graduate School at the link

Interested candidates may contact Kate Beard for further information. Rolling applications are being accepted for Fall 2018 enrollment.

The University of Maine is an Affirmative Action/Equal Opportunity Employer and the University especially encourages applications from women and minorities.

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