AI Powered Firearm Detection Software

The vendor is required to provide AI-powered firearm detection solutions for information gathering and market research. 
- Software solutions capable of using existing or new IP-based video streams to detect visible firearms in real time and alert operators for appropriate intervention.
•    Operate on existing sky watch tower video infrastructure with minimal hardware upgrades. 
•    Detect visible firearms (handguns, long guns, rifles) carried openly or brandished. 
•    Reduce false positives through AI and ML model training and analytics. provide reliable alerting within seconds to operators and integrated dispatch systems. 
•    Maintain compliance with applicable state and federal privacy standards. 
•    Solutions may be cloud-based, on-premise, or hybrid, and may include subscription or perpetual licensing models.
a. Product capabilities
•    Types of firearms detectable (handgun, rifle, shotgun, etc.).
•    Detection range and accuracy using fixed, PTZ, or mobile camera feeds.
•    Real-time alerting capabilities (e.g., local alerts, SMS, email, cad integration).
•    False positive and false negative rates in operational environments.
•    Performance in low light, crowd density, and adverse weather conditions.
•    Compatibility with commonly used video management systems (VMS).
•    Capability to integrate with sky watch tower video streams and similar deployments.
•    Options for edge vs. cloud processing.
b. System requirements
•    Minimum camera resolution and frame rate for optimal detection.
•    Network bandwidth requirements.
•    Server, GPU, or cloud compute requirements (if applicable).
•    Cybersecurity measures and data encryption standards.
•    Country based data storage options and compliance (if applicable).
c. User interface and analytics
•    Centralized dashboard or console for monitoring alerts.
•    Event logging and export capability for forensic analysis.
•    Ability to review detections and retrain AI models to reduce false positives.
•    Multi-site or statewide scalability.
d. Deployment and support
•    Implementation timeline and recommended pilot approach.
•    Training requirements for operators and IT staff.
•    Warranty, software maintenance, and support offerings.
•    Update frequency for AI model improvements.
e. Pricing information
•    Indicative pricing model (subscription, perpetual license, SaaS).
•    Expected costs for pilot program (if offered).
•    Expected annual operating costs.
f. References and case studies
•    Examples of prior deployments (schools, municipalities, public safety).
•    Lessons learned or case studies showing real-world results.

- Questions/Inquires Deadline: September 19, 2025