Crowdsensing

1. CROWDSENSIN
G
Eng: Ahmed Ayman Fahmy

3. OUTLINE
 Introduction
 Crowdsensing
 Mobile crowdsensing applications
 Challenges of Crowdsourcing
 Future research direction
 Conclusion
 references

4. INTRODUCTION
 In recent years, there is a lot of sensing devices emerged in our life and creating IOT
( internet of things).
 IOT has drown a great attention, it is expected to create a world where all objects
around us are connected to the internet.

5. CROWDSENSING
 Today approximately all humans
have mobile phones capable of
sensing and computing so
crowdsensing is a new model which
allow to uses these phones extract
information and share data between
their users to measure, analyze, map
and predict phenomena of common
interest.
 Types of devices
Smartphones.
Wearable devices.
 in-vehicle sensor devices (GPS).

6. CROWDSENSING

7. CROWDSENSING (CONT.)
 Devices is equipped with various
sensors, most smart phones can sense
Noise (microphone)
Location (GPS)
Movement (accelerometer)
Temperature more and more

8. CROWDSENSING (CONT.)
 Types of crowdsensing
Participatory crowdsensing :- users of the sensing devices manually
sending data to the servers.
Opportunistic crowdsensing:- collected data is sent automatically to
the servers without user intervention.

9. CROWDSENSING (CONT.)
Mobile crowdsensing procedures:
Data collection.
Data storage.
Data upload.
 There are three main strategies for collecting data:
The user of device collect data manually (Taking photos)
Data collection is partially controlled by the user.
A device begins to collect data when the user is in a particular place
at a particular time.

10. CROWDSENSING (CONT.)
Deduplication
 It is used to eliminate the redundant data when we are in the
collection phase to improve the QoS, reduce cost of implementation
and save resources.
 It perform filtering and compressing function to the data that has
been collected before it gets uploaded.
 Types of data deduplication
Real-time deduplication
Post process deduplication

11. MOBILE CROWDSENSING
APPLICATIONS
MCS Apps
Environmental Infrastructure
1.Social
application

12. MOBILE CROWDSENSING
APPLICATIONS
 Environmental crowdsensing used to
measure the natural of environment
like
 Air temperature
 Noise Pollution
 Air pollution
 Weather Conditions

13.  infrastructure crowdsensing used to measure the public infrastructure
 Traffic congestion
 Road condition

14. MOBILE CROWDSENSING
APPLICATIONS
 Social crowdsensing it is used to measure data about social life of individuals

15. CHALLENGES OF
CROWDSENSING
 Automated configuration of sensors.
 Resource limitations (Energy consumption, bandwidth )
 Privacy, security and integrity.

16. FUTURE RESEARCH
DIRECTION
 Optimization of multiple factors like localization, prediction and energy
budget.
 Privacy protection
 Social internet of things.

17. CONCLUSION
 Mobile crowdsensing plays an important role in the IoT .
 Crowdsensing can provide a lot of information to the community about the area of
interest.
 Sensors continuously generate a lot of data, which consumes much resource, such as
storage resource for storing data and bandwidth resource for data transfer.
 Redundancy elimination of sensor data is important to reduce the storage and
bandwidth and increase quality of service (QoS).

18. ‫هريرة‬ ‫أبي‬ ‫عن‬-‫عنه‬ ‫هللا‬ ‫رضي‬-‫هللا‬ ‫رسول‬ ‫أن‬-‫عليه‬ ‫هللا‬ ‫صلى‬
‫وسلم‬-‫قال‬" :‫ثالث‬ ‫من‬ ‫إال‬ ‫عمله‬ ‫انقطع‬ ‫آدم‬ ‫ابن‬ ‫مات‬ ‫إذا‬:‫صدقة‬
‫أو‬ ،‫جارية‬‫به‬ ‫ينتفع‬ ‫علم‬‫له‬ ‫يدعو‬ ‫صالح‬ ‫ولد‬ ‫أو‬ ،"

20.  Jinwei Liu, Haiying Shen, Xiang Zhang “A Survey of Mobile Crowdsensing
Techniques: A Critical Component for The Internet of Things “
 R.K. Ganti, F. Ye, and H. Lei. Mobile crowdsensing: Current state and
future challenges. IEEE Comm. Mag., 49(11):32–39, November 2011.
 C. C. Aggarwal, Y. Xie, and P. S. Yu. On dynamic data-driven selection
of sensor streams. In Proc. of KDD, pages 1226–1234, 2011.