This document discusses mobile crowdsensing and its applications. It begins with an introduction to crowdsensing and the rise of sensing devices and the Internet of Things. It then describes how crowdsensing uses smartphones and other mobile devices to collect and share data. It discusses challenges like resource limitations and privacy. It also outlines potential applications in environmental monitoring, infrastructure monitoring, and social applications. It concludes by discussing future research directions such as optimization techniques and privacy protections.

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.