Smart Crowd Analyzer is a real-time system for indoor crowd analysis. The system is implemented based on a people counter, that detects individuals as well as group of individuals. With bi-directional counting, age and gender determination; as well as regular customer detection system; it proves to be an ideal mechanism for crowd analysis. All these analysis are then reported on a website that provides stats and business insights to its users.

1. Department of Electrical Engineering,
University of Engineering and Technology, Lahore
Smart Crowd Analyzer
Group No: 02
Project Advisor: Dr. Ubaid Abdullah Fiaz
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

2. Team Introduction
Hamda Anees (Team Leader)
2017-EE-007
Specialization: Computer
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021
Mehrunisa Ashraf
2017-EE-0002
Specialization: Computer
Haris Rafique
2017-EE-024
Specialization: Computer
Shahkar Ul Hassan
2017-EE-036
Specialization: Computer

3. Problem Statement
• Over the last decade, retailers are facing significant
obstacles, such a staff planning, unavailability of
stocks, accumulation of unwanted items, and the
inability to accurately forecast demands, etc. All these
problems result in poor performance/sales, and
ultimately, result in profit loss.
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

4. Proposed Solution
This proposed project is modeled upon a people counter,
namely, “Smart Crowd Analyzer”, which is a bidirectional
wireless crowd analysis device based on a smart-cam that
analyses crowd features using artificial intelligence and deep
learning algorithms. The project is based on prior research
with the addition of embedded features such as group
detection, age detection, gender determination, regular
customer detection, and staff exclusion. After analysis of the
physical traits, an analytical report is generated, that provides
retailers with deep insights analysis and tracking in retail
operations.
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

5. Benefits of People Counter
Stock Management
 Sales Conversion
Visual Surveillance
Customer Behavioral Analysis
Staff Schedule Planner
Public Space Designing
Retail Analysis Report
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

6. Features
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021
Gender Detection
Regular Customer Detection Age Detection
Group Detection
Applications

7. Architecture
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021
1. Capture Real-time video through a surveillance camera.
2. Data will be passed along a series of algorithms.
3. On basis of algorithm, we will detect; gender, age, no.
of people entering/exiting, no. of group (of people),and
time interval.
4. Generate Real-time stats, visuals (such as charts,
tables).
5. Generate a website to monitor daily, weekly, and
monthly progress and analysis report.

8. Bi-Directional
People Counter (3)
Flow Diagram

9. Bi-
Directional
Counter
Boundary
Box
Object
Detection
Block Diagram
Object
Tracking
People
Count

10. Working Preview
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

11. What we have done so far?:
Implementation of the following algorithms:
 Age Detection
 Gender Detection
 Regular Customer Detection
 Bi-Directional Counter
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

12. Implementation of Gender & Age Detection
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

13. Implementation of Regular Customer
Detection
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

14. Implementation of Bi-Directional Counter
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

15. Gantt Chart
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

16. Software Developed
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

17. Software Developed
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

18. Future Deliverables
• Currently, we are working on making an effective
database system for our website.
• Moreover, the sales conversion and marketing features
needs to be deployed.
• Other features that we are considering to introduce are:
 Heatmaps
 Cyber-Security
 Face-Mask Detection
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021

19. References
Undergraduate Final Year Project Presentation
Dated: 15th January, 2021
[1] H. Bischof B. Wachmann, W. Kropatsch. ”evaluation of people counting systems”, january 2001.
[Online].Available:https://www.researchgate.net/publication/246112302_Evaluation_of_people_cou
nting_systems, Accessed June 20, 2020.
[2] M. Akcay H.H. Cetinkaya. ”people counting at campuses”, procedia - social and behavioral
sciences,vol.183,pg.732-736,May13,2015.[Online].
Available:https://www.sciencedirect.com/science/article/pii/S1877042815030967?via%3Dihub,Acce
ssed June 20, 2020.
[3] Nithya Roopa. S. ”emotion recognition from facial expression using deep learning”,international
journal of engineering and advanced technology (ijeat), pg.2249 – 8958, vol. 8, issue 6. August
2019.
[4] Dr Anuradha S G Shivashree G. ”crowd analysis using computer vision techniques”,
international journal of engineering research in computer science and engineering (ijercse) ,vol 5,
issue 4, april 2018. [Online]. Available:https://ieeexplore.ieee.org/ document/5562657/, Accessed
June 20, 2020.