1. This research was made possible with the support of the Indiana University-Purdue University Indianapolis Department of Computer Information and Information Science, as well as through funding from the National Science
Foundation and the United States Department of Defense. The authors would like to thank their mentor, Hongbo Liu, as well as Dr. Feng Li, Dr. Eugenia Fernandez, and Sheila Walter for their support.
Smart City Surveillance Running on Vehicles
Introduction Method
Future Work
Although we can connect clients
to the server, in the future we
would like to have the server
connect to and communicate with
clients and Android devices as well.
Additionally, we would like to
have the server be able to dictate a
trajectory to clients so that data
can be collected about a requested
area.
Completed Tasks
In its current state, the smart city
surveillance system has a server that
accepts clients, as well as the queries that
those clients send to it. The server can
access the MySQL database to save
queries or information. The server can
respond to clients and dictate vehicle
target locations. Additionally, the database
can send data to clients as well as retrieve
vehicle locations.
References• C. (2016, June 21). Smart City Illustration [Digital image]. Retrieved July 15, 2016, from
http://www.geospatialworld.net/understanding-smart-city-solutions/
• Pavlov, D. V., Dr., & Lupu, E., Dr. (2013). Hive: An Extensible and Scalable Framework
For Mobile Crowdsourcing (Rep.). London: London Imperial College.
• Smart City [Digital image]. (n.d.). Retrieved July 15, 2016, from images.google.com
The urban population of the United States
has been increasing over the last several
years. To manage the needs of expanding
cities and their citizens, this proposes the
development of a model for smart city
surveillance that runs on vehicles by utilizing
a variety of vehicle-mounted sensing
capabilities. The model aims to crowdsource
real-time urban events. Vehicles are the
logical choice for this endeavor, as the
technology present in current models has
continued to expand and include many
features such as GPS services and mobile
phone interactions.
Additionally, the development of vehicle-
mounted cameras has made collecting a vast
amount of data on not only images, but also
position and acceleration easier. Thus,
vehicles with mounted cameras will leverage
existing communication and sensing
infrastructure to collect data about events in
their environment. Once collected, the data
contributed from multiple participants can
then be uploaded to a cloud server to
develop a detailed view of an event as well
as provide significant statistics about urban
communities. The cloud server will contain a
database filled with requests, conditions,
and vehicle target locations. This information
will then be made accessible to the public via
connection to this server. The system
performs efficiently keeping client wait times
low even as workload increases.
The surveillance program uses a 12-byte query format to send data between clients and the server. This
query, once received and examined by the server, is inputted into a MySQL database. The MySQL database
holds road conditions and vehicle locations sent from clients, so this data can be accessed by other clients
when assessing traffic and travel patterns for day-to-day needs. A timestamp algorithm keeps track of the
time at which any requests for data input to the database are made by clients. The server can also support
concurrent query handling, which means multiple clients can connect to the server at once and send data
about road conditions and vehicle locations.
Performance Evaluation
The above graph demonstrates that
our surveillance system can
adequately handle a large number of
client connections. The median wait
times remain at similar levels as the
number of clients increase.
System Design
Ma’ayan Doron, Sam Canner, Alex Canner
Purdue University School of Engineering
Indiana University-Purdue University Indianapolis
Hongbo Liu
Figure 1: The 12-byte query format clients use to
send data to the server
Figure 2: An overview of the data structure used
to share data between the server and clients
Figure 3: An overview of the client-side
of the surveillance program
![This research was made possible with the support of the Indiana University-Purdue University Indianapolis Department of Computer Information and Information Science, as well as through funding from the National Science
Foundation and the United States Department of Defense. The authors would like to thank their mentor, Hongbo Liu, as well as Dr. Feng Li, Dr. Eugenia Fernandez, and Sheila Walter for their support.
Smart City Surveillance Running on Vehicles
Introduction Method
Future Work
Although we can connect clients
to the server, in the future we
would like to have the server
connect to and communicate with
clients and Android devices as well.
Additionally, we would like to
have the server be able to dictate a
trajectory to clients so that data
can be collected about a requested
area.
Completed Tasks
In its current state, the smart city
surveillance system has a server that
accepts clients, as well as the queries that
those clients send to it. The server can
access the MySQL database to save
queries or information. The server can
respond to clients and dictate vehicle
target locations. Additionally, the database
can send data to clients as well as retrieve
vehicle locations.
References• C. (2016, June 21). Smart City Illustration [Digital image]. Retrieved July 15, 2016, from
http://www.geospatialworld.net/understanding-smart-city-solutions/
• Pavlov, D. V., Dr., & Lupu, E., Dr. (2013). Hive: An Extensible and Scalable Framework
For Mobile Crowdsourcing (Rep.). London: London Imperial College.
• Smart City [Digital image]. (n.d.). Retrieved July 15, 2016, from images.google.com
The urban population of the United States
has been increasing over the last several
years. To manage the needs of expanding
cities and their citizens, this proposes the
development of a model for smart city
surveillance that runs on vehicles by utilizing
a variety of vehicle-mounted sensing
capabilities. The model aims to crowdsource
real-time urban events. Vehicles are the
logical choice for this endeavor, as the
technology present in current models has
continued to expand and include many
features such as GPS services and mobile
phone interactions.
Additionally, the development of vehicle-
mounted cameras has made collecting a vast
amount of data on not only images, but also
position and acceleration easier. Thus,
vehicles with mounted cameras will leverage
existing communication and sensing
infrastructure to collect data about events in
their environment. Once collected, the data
contributed from multiple participants can
then be uploaded to a cloud server to
develop a detailed view of an event as well
as provide significant statistics about urban
communities. The cloud server will contain a
database filled with requests, conditions,
and vehicle target locations. This information
will then be made accessible to the public via
connection to this server. The system
performs efficiently keeping client wait times
low even as workload increases.
The surveillance program uses a 12-byte query format to send data between clients and the server. This
query, once received and examined by the server, is inputted into a MySQL database. The MySQL database
holds road conditions and vehicle locations sent from clients, so this data can be accessed by other clients
when assessing traffic and travel patterns for day-to-day needs. A timestamp algorithm keeps track of the
time at which any requests for data input to the database are made by clients. The server can also support
concurrent query handling, which means multiple clients can connect to the server at once and send data
about road conditions and vehicle locations.
Performance Evaluation
The above graph demonstrates that
our surveillance system can
adequately handle a large number of
client connections. The median wait
times remain at similar levels as the
number of clients increase.
System Design
Ma’ayan Doron, Sam Canner, Alex Canner
Purdue University School of Engineering
Indiana University-Purdue University Indianapolis
Hongbo Liu
Figure 1: The 12-byte query format clients use to
send data to the server
Figure 2: An overview of the data structure used
to share data between the server and clients
Figure 3: An overview of the client-side
of the surveillance program](https://image.slidesharecdn.com/ec361702-abbb-44df-a55f-514cb7b1a10f-160819144715/85/smart-city-surveillance-running-on-vehicles-1-320.jpg)
