際際滷

際際滷Share a Scribd company logo

Home work

Download as PPTX, PDF
S
shengchikuo

This document proposes a smart city system using facial recognition on surveillance cameras to track criminal suspects in real-time. It outlines the current manual process police use to search surveillance footage which is time-consuming. The proposed system would use machine learning to create a facial recognition model trained on a government database. This would allow the system to automatically detect and track suspects on cameras, informing police instantly of their location. Benefits mentioned include increased safety, reduced crime rates, and time savings for both the public and law enforcement.

1 of 30
Download to read offline
Smart City Face recognition base on surveillance monitor and big data that able to track suspects
Outline Introduction Body Feasibility analysis. Scientific evidence. How generic people benefited from this idea. Reference Conclution
Idea introduction Difference between the approach in nowaday and the conceptual illustration
Nowaday approch fig (1) Current practices in electronic surveillance 1. 2. 3. 4. Police have to access to all surveillance cameras manually.
Nowaday approch fig (1.1) Current practices in electronic surveillance 1. 2. 3. 4. 1. Determine where the suspect may appear
Nowaday approch fig (1.2) Current practices in electronic surveillance 1. 2. 3. 4. 2. Access the surveillance on the path
Nowaday approch fig (1.3) Current practices in electronic surveillance 1. 2. 3. 4. 3. Capture and organize videos for a specific time period and then assign tasks
Nowaday approch fig (1.4) Current practices in electronic surveillance 1. 2. 3. 4. 4. Watch video manually and try to find where the suspect is.
What is the problem? Time consuming. suspect may run far away during the period of watching video human may fail to recognize the face with confusing by wearing different cloth suspect.
The illustration of face recognition in surveillance monitor fig (2) Using machine learning to create face recognition system 1. 2. 3.
The illustration of face recognition in surveillance monitor fig (2) Using machine learning to create face recognition system 1. 2. 3. Collect the face into government data management system
The illustration of face recognition in surveillance monitor fig (2) Using machine learning to create face recognition system 1. 2. 3. Machine learning to training facial regonition model.
The illustration of face recognition in surveillance monitor fig (2) Using machine learning to create face recognition system 1. 2. 3. Cloud system will imform the police where the suspect is, once the system find the specific person.
Interesting for General Public Safe life Reduce crime rates
Interesting for General Public Enegy efficiency Saving time
Interesting for CS/CE Students The active of samrt city bring.. Employment Career Opportunities More funding for research
Example of SMART CITY technorogy Anylsing data from surveillance cameras Using for tracking offenders ! Using for preventing crime !
Importantance of IoT Improving convenience More efficiency cost economy
Example of current IoT technology... Door lock system air conditioner etc...
Importance of BIG DATA Build database human face database Data analyzing facial recognition
BIG DATA Management Outline Your Goals Data Protection NEW WAY OLD WAY Adapt to the New Changes
Facial Recognition
Facial Recognition source : ccw1986.blogspot
Short Video https://www.youtube.com/watch?v=zMhHsaHR8oA
Challeng e Cheaper Device Privacy problem Power Saving IoT
Reason of FailBudget Data collection
Future of SMART CITIES More business opportunities
Layout of Prestation
map
Refference Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNN BALANCING OF NEEDS BETWEEN :SECURITY AND PRIVACY ENGLAND Identify and Trace Criminal Suspects in the Crowd Aided by Fast Trajectories Retrieval Face recognition-based real-time system for surveillance

More Related Content

Home work

Editor's Notes

  • #15: Q1 Why is the topic of SMART CITIES interesting for the general public?
  • #16: Q1 Why is the topic of SMART CITIES interesting for the general public?
  • #17: Q2 Why is the topic of SMART CITIES interesting for computer science/engineering students?
  • #18: Q2 Why is the topic of SMART CITIES interesting for computer science/engineering students?
  • #19: Q3 How is the IoT the most important feature of SMART CITIES?
  • #20: Q3 How is the IoT the most important feature of SMART CITIES?
  • #21: Q4 How is BIG DATA a very important feature of SMART CITIES?
  • #22: Q4 How can the BIG DATA be better managed in the context of smart cities?
  • #23: Q5 Explain a specific technology used in the smart city context.
  • #24: Q5 Explain a specific technology used in the smart city context.
  • #25: Q6 Demonstrate a short YouTube movie explaining the ongoing research and accomplishments on the topic.
  • #26: Q7 Why is the research on the issue so challenging and difficult?
  • #27: Q7 Why do most smart cities fail across the world?
  • #28: Q8 What research needs to be done in the future on SMART CITIES?
  • #29: Q9 Show how you have used the MIND MEISTER software to plan the layout of the presentation.