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Feasibility Study Of Continuous Real-Time Spatial Interpolation Of Phenomena Using Built-In Functionality Of a Commercial Data Stream Management System
Adoption of smartphones and tablets has made users crave the latest information at all times. People extensively rely and use these mobile devices to know what is happening in their surroundings. They have a dual role to play: they get information and also can act as sensors, that can share data. This is made possible due to the integration of low-cost, microsensors like accelerometers, proximity sensors, GPS, ambient light sensors, compasses, etc. However, in the near future it is possible that environmental sensors like those measuring humidity, temperature, particulate matter, or radiation levels, might be included and allow mobile devices to act as mobile stations that can monitor and share observations of phenomena in their surroundings. Such applicability means that spatial interpolation of the mass-measured phenomena must be done at near real time so that users can also be clients ‘seeing’ the entirety of the phenomenon in their vicinity.
Managing such mass data updates from mobile sensors requires novel data management technology that can keep up with processing this data onslaught, i.e. data stream management systems. There are a few out-of-the-box DSMS solutions offered by industries today. Some prominent ones are Esper, IBM InfoSphere Streams, Microsoft StreamInsight, Oracle CEP, and StreamBase. However, not much work has been done on how a DSMS can be used to perform real-time spatial interpolation of continuous phenomena. The project explores whether real-time spatial interpolation of a continuous phenomena based on point-based sensor data streams can be accomplished by using the off-the-shelf functionalities available in commercial DSMS available today. The project also introduces the concept of spatial field data model, which provides a robust and an extensible framework to define fields and their behavior. Finally, a DSMS application was built and tested with simulated data from the Fukushima nuclear plant accident in Japan 2011. Experiments were conducted to test the performance and analyze the bottlenecks of using a commercial DSMS.
Spatial Analysis on Nuclear Radiation Data (11 March 2011, Fukushima Diiachi)
On 11 March 2011, around 2:46 p.m. local time, near the Japanese island of Honshu was an earthquake of 9 on the Richter scale. The earthquake resulted in a tsunami which caused a series of nuclear meltdown and release of radioactive materials into the atmosphere in and around Fukushima Daiichi. It was the largest nuclear disaster since Chernobyl of 1986.
The objective of this report is to perform exploratory analysis on the radiation dataset using R and to perform spatio-temporal interpolation using kriging.Space-Time/3D analysis is a more realistic model to perform interpolation of natural phenomenon. Such a model takes into account both space and time dimensions, thereby creating a more robust model.
Spatial Field Visualization & Implementation
The purpose of this project is two-fold: to develop a system for representing a generic Spatial Field in an application, and a means for visualizing that data once stored. A generic Spatial Field allows the data stored within to be leveraged for many different purposes depending on the data, the application and the needs of the user. It is for this reason that a new model had to be defined. The system we put forth broadly utilizes a data stream model for input processing. Furthermore the system must: filter the input stream based on a specified query or queries, group the data into time-based windows, convert the contents of each window into a Spatial Field, and materialize the result as an image. To this end we selected Oracle CEP as the application server for the development of our project. Oracle CEP works in conjunction with Eclipse and allowed us to design our data stream architecture. Oracle CEP contains many of the elements found in competing DSMS packages, including a visual representation of the workflow.
Mobile Data Stream based Spatial Interpolation of Continuous Environmental Phenomena
A novel approach to reduce traffic in a heterogeneous network using a common Gateway
MediSmart
MediSmart is a system used to assist the elderly in taking their medications on time, scheduling medical
appointments, and arranging transportation. The system is facilitated by a series of user preferences that
interact in such a manner as to make accomplishing these tasks as simple and seamless as possible. This project was a design prototype for next generation applications which aimed at leveraging all the multimodal interaction modes, such as sound, vibration, color, light etc that are currently available in a standard smartphone. The application was built in android 2.1 platform.
ABSTRACT (unpublished work)
Technology advances have created a large variety of novel, inexpensive sensors in the millimeter range that can be attached to or embedded into smartphones. Via smartphones the sensors can be directly connected to the Internet and enable us to collect high frequency updates of potentially thousands of mobile sensors densely deployed over a larger urban area. This crowdsourcing approach to real-time environmental data collection can produce a vast number of concurrent sensor data streams that challenges traditional processing strategies using DBMS and GIS requiring real-time data integration and analysis. In the last decade, data stream management systems (DSMS) have been introduced as powerful data processing tools for applications with update rates of 100,000-500,0000 tuples/s. In this paper, we investigate extending DSMS for continuous window query processing that achieves real-time spatial interpolation of environmental phenomena such as air quality or air borne toxins based on up to 250,000 of individual mobile sensor data streams. We propose several different strategies to optimize a pipelined stream operator approach to achieve near-real-time spatial interpolation investigating memory footprint, runtime efficiency and interpolation quality of the different strategies.
Authors: Silvia Nittel, J.C. Whittier, Qinghan Liang, Balaji Venkatesan, Sytze de Bruin
ABSTRACT
In heterogeneous wireless networks, mobile users are able to move from their home networks to different foreign networks while maintaining access capability to their subscribed services, which refers to global mobility. This is vital as the globe is too big for a single network to cover. One of the key challenges in global mobility management is intersystem location management, which consists of keeping track of mobile users who roam into foreign networks.
We propose an interoperable architecture for mobility management in heterogeneous wireless networks and introduces the use of a specialized memory based internetworking Gateway that interconnects the two different subsystems. The internetworking Gateway involves collecting information about the subscriber and analyzing this information to build a cache table where the users with maximum foreign network visits are stored. Furthermore it groups multiple registration requests destined to a common destination into a single registration request. Once registered the internetworking Gateway handles the subsequent requests of the registered mobile user, thereby reducing the overall signaling cost incurred for the registration process.
Work-study vs non-work study job analysis in the University of Maine campus using CAD files in ARCGIS 10
The aim of the project is to analyze the various job positions available in the University of Maine campus, especially to students. There are two types of work that are available to students namely- work study and non work study. An international student can only work in non work study job. Work study job is one funded by the federal and so only native students are eligible to apply, whereas non work study job is funded by the individual department and so both native and international students can apply. Therefore, for a new international student this project can serve as a guide tool to sort departments and jobs to which he/she would like to apply for.
Also, the Career link portal does provide jobs that are currently available in the campus, but it is no surprise that there are still many jobs which are not posted by departments around the campus. So, the project results can help a student looking for a particular job to visit the department which has a history of his/her related job.
GE Smallword OpenStreetMap web connector
OpenStreetMap is a free mapping service that can be used for commercial/non-commercial applications.Contains data which can be rendered and edited. Some key properties of map data include:
Zoom levels normally vary between 0-18
X goes from 0 (left edge is 180 °W) to zoom -1 (right edge is 180 °E)
Y goes from 0 (top edge is 85.0511 °N) to zoom -1 (bottom edge is 85.0511 °S)
Both x and y are longitude and latitude.
The osm map tile are 256x256 pixel PNG images. File url format for accessing a tile is zoom/x/y.png
This internal project was done in Red Planet Consulting in 2011 using C#, Magik programming languages and a demo was implemented in GE Smallworld cambridge database.
Phobos, a java based desktop application
Phobos is a java map viewer application with thematic mapping functionality using Cambridge demo data. It was developed using Oracle MapViewer 10.1.3.1 (a map server) and MapBuilder 10.1.3.1 (style management) application. Basic functionality of map browsing like zoom, pan, select, identify, home bookmarks and print tools were implemented. Also theme visibility tool was implemented to turn on/off any theme or table. Additionally, a themaic mapper tool was implemented which basically can help to create new themed maps based upon an attribute using gradient or chosen color values. The project was completed in Red Planet.
