Cloud Computing Major Project

1. Team-16
Madan Jhawar(201202018)
Darpan Baheti(201202036)
Shrenik Jain(201403006)
Arsh Anand(201405531)
CLOUD COMPUTING
MAJOR PROJECT
A REAL TIME EVENT MONITORING
SYSTEM USING APACHE SPARK
STREAMING

2. INTRODUCTION
● Event Monitoring is the process of collecting, analyzing and signalling event
occurrences which may stem from arbitrary sources in both hardware or
software.
● Event Monitoring is used to analyse the change in the behaviour of a
particular object.
● The Object which is monitored is called the Monitored Object.
● A Monitored object must be properly conditioned with event sensors to enable
event monitoring.

3. ABOUT THE PROJECT
● Our aim is to build a Real Time Vehicle Monitoring System.
● Incidents of Road Rage have increased considerably over the last decade
resulting in many casualties.
● Most of these casualties can be attributed to the long response time required
to reach the place of accident.
● This is due to the fact that the process of determining the location of the
accident and communication with the concerned authorities is quite lengthy.

4. OBJECTIVE
● Reduce the time required to report an accident and to determine its
location more precisely.
● Monitor Real-Time GPS Data to identify possible accident locations.
● Monitor sensor data to keep a check on speed limits.
● Notifying the concerned authorities in case of anomaly or potential
accident.

5. DESCRIPTION
● The idea is to make location identification automatic in order to reduce the
response time in case of an accident.
● Vehicular Sensors are attached to each of the vehicles.
● These sensors send a continuous stream of real-time data containing relevant
information about the position(in terms of longitude and latitude) and speed of
the corresponding vehicle.
● The underlying algorithm will look for certain anomalies in data such as
sudden drop in speed of the vehicle.

6. TECHNOLOGIES USED
● Python
● Apache Spark Streaming
● Open Street Maps Integration

7. APPROACH
● Firstly we need to simulate the vehicular sensors.
● For this we generated random data using a python script.
● This data was generated at an interval of 15 seconds.
● It contained all relevant information about a particular vehicle like its GPS
coordinates, speed etc.
● Apache spark streaming server is used to collect and analyse the incoming
data from these sensors.

8. ● The incoming data is processed by the spark streaming server.
● This data is then plotted on the map to look for possible accident spots.
● Following three kinds of markers are used in the map
○ Red Marker- This indicates the location where accident has actually
occurred.
○ Yellow Marker- This indicates about speed limit crossing.
○ Blue Marker- This indicates about the heavy traffic in a particular
location.

9. DESIGN

10. SCREENSHOTS

12. CONCLUSION
Real-time visibility into driver behavior
Monitor driver speeds
Detailed event records
Ability to set alarm criteria