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Emergency Management through 
Sensors of Enterprise Systems 
Deniz Gurkan, Kiran Vemuri, Parth Gala, Anatoliy Malishevsky,...
Outline 
 Motivation 
 Introduction 
 Data sharing needs for emergency decision making 
 Data storage 
 Our Proposed ...
Motivation 
 Emergency management is time sensitive 
 Utilize all the information sources available to the emergency ope...
Introduction 
To forecast or respond to an emergency without 
enough information can be as efficient as trying to 
solve a...
Collecting data and facilitating data exchange between 
various enterprise systems and sensors by stitching them 
together...
Data storage 
Collecting the data into a regular RDBMS would make the 
data redundant and make it an overhead because of t...
IF-MAP: Facilitate Data Exchange 
Defines a standard interface between any product 
or system and a so called metadata acc...
IF-MAP Advantages 
 Graph database implementation - simple 
 Client – Server architecture with sessions for every client...
UH – Emergency Management Portal 
University of Houston’s emergency management projects aims to integrate data from system...
How? 
Multiple methods: 
 Use API’s if they’re open and available. 
 Polling databases 
 Bump in the wire 
 Parsing da...
Integration status 
Door access systems : Bump in the wire 
 Alerts on door access decisions ( grant/deny) 
 Alerts on l...
Integration status cont. (Work in progress) 
 Facilities – alerts from fire alarms, moisture sensors/leak detection equip...
Conclusion and future outlook 
Incident heat map
Questions?
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Emergency Management Through Sensor of Enterprise Systems

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Presentation at IEEE Sensor Apps Symposium 14: Emergency Management Through Sensor of Enterprise Systems

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Emergency Management Through Sensor of Enterprise Systems

  1. 1. Emergency Management through Sensors of Enterprise Systems Deniz Gurkan, Kiran Vemuri, Parth Gala, Anatoliy Malishevsky, and Anand Daga
  2. 2. Outline  Motivation  Introduction  Data sharing needs for emergency decision making  Data storage  Our Proposed Integration  IF-MAP  Integration status  UH – Emergency management project  Conclusion and future work
  3. 3. Motivation  Emergency management is time sensitive  Utilize all the information sources available to the emergency operations centers.  Data from diverse enterprise systems deployed around the campus can help speed up the process of emergency management.
  4. 4. Introduction To forecast or respond to an emergency without enough information can be as efficient as trying to solve a puzzle without enough pieces. Different enterprise systems and sensors deployed around the campus can serve as information sources for the emergency operations center to help take better decisions.
  5. 5. Collecting data and facilitating data exchange between various enterprise systems and sensors by stitching them together and intelligently generating alerts and associations to be displayed on a common display platform can help improve the emergency management procedures.
  6. 6. Data storage Collecting the data into a regular RDBMS would make the data redundant and make it an overhead because of the time it takes to constantly store and retrieve data. Use of METADATA can drastically improve the time complexity of the system as it is light, simple and fast.
  7. 7. IF-MAP: Facilitate Data Exchange Defines a standard interface between any product or system and a so called metadata access point, which is a database for aggregating, correlating, and distributing metadata between different systems in real time. Lightweight and supports three primitive operations: publish, subscribe, and search.
  8. 8. IF-MAP Advantages  Graph database implementation - simple  Client – Server architecture with sessions for every client - secure  No pre-determined schema  Run-time changes to schema – no downtime  No changes in the authoritative systems
  9. 9. UH – Emergency Management Portal University of Houston’s emergency management projects aims to integrate data from systems like card reader systems, camera systems, power systems etc., available on the campus to publish alerts to the emergency operations center and later try to relate and perform analytics on the data to intelligently predict possible emergencies.
  10. 10. How? Multiple methods:  Use API’s if they’re open and available.  Polling databases  Bump in the wire  Parsing data files
  11. 11. Integration status Door access systems : Bump in the wire  Alerts on door access decisions ( grant/deny)  Alerts on lockdowns  Alerts on door forced open statuses  Alerts on door left open Police dispatch : Database polling  Alerts on all the police dispatch events like burglary, weapons, rescue, etc…  Classification of alerts based on how critical the events are. Camera systems : geographical location and access records  Buildings on the map linked to floor plans and cameras positioned in the respective floors.
  12. 12. Integration status cont. (Work in progress)  Facilities – alerts from fire alarms, moisture sensors/leak detection equipment etc..,  Network – alerts to indicate network failure and the devices effected.  Power – alerts to indicate power failure, areas/buildings effected and identify the cause.
  13. 13. Conclusion and future outlook Incident heat map
  14. 14. Questions?

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