Intelligent Video Surveillance & Analysis

Intelligent Video Surveillance & Analysis

Roles and Responsibilities:

• System Design & Architecture:

  Participate in the design and architecture of intelligent video surveillance systems, including camera selection, placement, networking, and storage solutions.

• Video Analytics Implementation:

  Configure, deploy, and manage advanced video analytics applications (e.g., object detection, facial recognition, behavior analysis, license plate recognition, crowd analysis, anomaly detection).

• System Integration:

  Integrate video surveillance systems with other security platforms (e.g., access control, alarm systems, VMS - Video Management Systems) and business intelligence tools.

• Data Analysis & Insights:

  Analyze video footage and data generated by surveillance systems to identify security threats, operational inefficiencies, and business trends. Generate reports and provide actionable insights.

• Performance Optimization:

  Monitor the performance and health of video surveillance systems and analytics platforms. Optimize configurations to ensure efficient processing and accurate results.

• Troubleshooting:

  Perform in-depth troubleshooting, debugging, and issue resolution for complex problems within the intelligent video surveillance infrastructure and analytics software.

• Proof of Concept (PoC) & Evaluation:

  Research and evaluate new video surveillance technologies, AI/ML models, and analytical tools. Conduct PoCs to assess their suitability for business needs.

• Policy & Best Practices:

  Contribute to developing and enforcing policies and best practices for video surveillance data retention, privacy, and security.

• Collaboration:

  Work closely with security teams, operations, IT infrastructure, and potentially law enforcement to support various initiatives and investigations.

Preferred Candidate Profile:

• Video Surveillance Expertise:

  Strong understanding and hands-on experience with modern

  video surveillance systems

  (IP cameras, NVRs, VMS).

• Video Analytics Knowledge:

  Solid experience with implementing and managing

  intelligent video analytics

  solutions and platforms.

• Networking Fundamentals:

  Good knowledge of networking concepts (TCP/IP, bandwidth, routing) as they pertain to video streaming and surveillance infrastructure.

• AI/ML Concepts (Plus):

  Basic understanding of AI/Machine Learning principles related to computer vision and video analysis is a significant advantage.

• Problem-Solving:

  Excellent analytical and problem-solving skills with a proactive approach to identifying and resolving technical and operational challenges.

• Technical Tools (Plus):

  Familiarity with relevant software tools for video processing, analysis, or scripting (e.g., Python, FFmpeg) is a plus.

• Communication:

  Strong verbal and written communication skills to articulate technical concepts and findings clearly to both technical and non-technical audiences.

• Education:

  Bachelor's degree in Computer Science, Electrical Engineering, Security Management, Information Technology, or a related technical field.