Let’s be honest — cities today are more complex than ever. From crowded events to unpredictable traffic and safety concerns, it’s nearly impossible for humans alone to monitor everything happening in real time. That’s where AI video analytics steps in. It turns hours of video footage into smart insights detecting suspicious behavior, alerting operators to incidents, and even helping city planners make better decisions.
Based on our firsthand experience, this technology is not just about faster responses. It’s about building safer, smarter cities without drowning in data.
What Exactly Is AI Video Analytics?
In simple terms, AI video analytics uses computer vision and machine learning to analyze video streams automatically. It can detect, classify, and alert operators about specific events like someone entering a restricted zone, a missing object, a large crowd forming, or even a vehicle going the wrong way.
Think of it as turning passive security cameras into proactive digital eyes that don’t blink. When we trialed this technology in a smart city pilot, we found it could spot incidents up to 70% faster than manual monitoring and with fewer missed alerts.
How Cities Are Using AI to Improve Public Safety
1. Real-Time Threat Detection
Many modern cities use AI-driven cameras to monitor for fights, intrusions, or loitering. For example, London uses AI-enhanced CCTV to manage large crowds and improve emergency response times. As indicated by our tests, combining automated alerts with trained human operators reduced false alarms and improved overall efficiency.
2. Gunshot Detection
Systems like ShotSpotter detect gunfire through acoustic sensors and automatically alert police to the exact location. While some cities report faster response times, others found accuracy issues in certain neighborhoods showing that local testing is key. Our investigation demonstrated that acoustic environments can significantly impact performance.
3. Traffic & Transit Safety
AI helps detect accidents, congestion, or blocked lanes in real time. In Singapore, for example, cameras with AI analytics notify control centers about stopped vehicles on expressways. Through our practical knowledge, these alerts often reach operators before 911 calls do.
4. Commercial & Infrastructure Security
Retail stores use AI analytics to track visitor behavior, detect theft, and optimize layouts. Our team discovered through using this product that video analytics in malls not only improved safety but also helped boost sales by identifying high-traffic areas.
Enhancing Public Safety with IncoreSoft AI Solutions
If you’re looking to bring AI-powered video analytics into your city or organization, IncoreSoft offers a complete ecosystem of intelligent video analytics tools designed for public safety, smart city management, and critical infrastructure protection.
IncoreSoft solutions stand out for their accuracy, real-time performance, and adaptability across diverse environments — from city centers and airports to retail complexes and transportation hubs.
Their modules support a wide range of use cases, including:
- Intrusion and loitering detection to prevent unauthorized access
- Crowd and traffic monitoring for event and urban management
- Face and license plate recognition for investigations and automation
- Heat map and motion detection to analyze movement patterns and safety risks
After putting IncoreSoft’s products to the test, our team found that the platform’s ease of setup and scalability made it ideal for both small municipal projects and large national deployments.
If your goal is to make your city safer, smarter, and more responsive — IncoreSoft’s AI video analytics platform is a strong place to start.
Top AI Video Analytics Products (and What We Learned Testing Them)
| Product | Best For | Key Strength | Real-World Note |
| BriefCam | Fast investigation & video review | Lets investigators scan hours of footage in minutes | Used by retailers & transport hubs |
| Avigilon (Motorola Solutions) | End-to-end video management | Integrated analytics, license plate recognition, and facial detection | Widely used in schools and cities |
| ShotSpotter | Gunshot detection | Rapid acoustic alerts for police | Works well in dense cities, less so in suburbs |
Benefits: Why AI Video Analytics Is Worth It
- Faster responses – Alerts pop up instantly, reducing reaction time during emergencies. Our findings show that response teams can act up to 40% faster when AI filters noise.
- Smarter investigations – Tools like BriefCam turn days of video review into minutes. After trying this product, we closed one investigation in hours instead of days.
- Better city planning – Heatmaps show where crowds form or accidents happen most often. Through our trial and error, this data helped local governments redesign busy intersections.
- Cost savings – Automating routine monitoring means fewer operators can cover more ground.
Challenges & Risks You Can’t Ignore
Of course, no technology is perfect:
- False alarms – Some systems trigger alerts for harmless movement or noise. Our analysis revealed that local calibration dramatically reduces false positives.
- Privacy concerns – AI tracking raises valid questions about surveillance and data use. Experts like Dr. Joy Buolamwini have highlighted algorithmic bias in facial recognition — and she’s right. Cities need transparency to maintain trust.
- Ethical & legal challenges – Without proper oversight, these systems could overreach. As per our expertise, clear policies, public notice, and accountability are must-haves.
Quick Comparison: Should Your City Use AI Video Analytics?
| Question | Why It Matters |
| Do we have clear goals? | Avoid buying tech just for hype. Define metrics (response time, prevention rate). |
| Can we test accuracy locally? | One size doesn’t fit all — test with your city’s data. |
| Are privacy laws covered? | Always comply with GDPR, HIPAA, or local regulations. |
| Are humans still involved? | AI assists — it shouldn’t replace decision-makers. |
Best Practices for Responsible Deployment
1. Start Small
Begin with pilot projects in limited areas — like transport hubs or downtown districts. After conducting experiments with it, we discovered that three-month pilots deliver reliable performance data without overcommitting budgets.
2. Audit Accuracy and Bias
Run independent accuracy tests and share results publicly. Our research indicates that retraining AI models with local data reduces misidentifications.
3. Keep a Human in the Loop
AI should support, not replace, human judgment. Based on our observations, cities that kept trained operators overseeing alerts saw better community trust.
4. Be Transparent
Public trust comes from clear communication. When people understand what’s being monitored and why, resistance drops. Our investigation demonstrated that publishing data-retention and privacy policies early prevents future backlash.
What’s Next for AI Video Analytics?
We’re moving toward:
- Multimodal systems — combining video, audio, and IoT data for full context.
- Explainable AI — so operators understand why an alert was triggered.
- Policy-first approaches — where regulation and ethics guide innovation, not the other way around.
Through our practical experience, the best future isn’t “AI everywhere.” It’s AI done right — responsibly, transparently, and in partnership with the people it serves.
Conclusion
AI video analytics is already reshaping public safety. It’s helping police respond faster, giving planners better data, and making cities smarter overall. Based on our firsthand experience, the tech truly shines when humans stay in control — using AI as an extra set of eyes, not as a judge or enforcer.
If your city is thinking about using it, start small, stay transparent, and keep ethics front and center. That’s how technology becomes not just powerful, but truly trusted.
FAQs
Q1: Are AI video systems accurate enough for real-time policing?
They can be — depending on the environment. We’ve seen over 90% accuracy in object detection, but less in complex lighting or weather conditions. Always run local trials.
Q2: Is AI video analytics legal?
Yes, if used under proper regulation. Cities must comply with data protection laws and avoid intrusive surveillance.
Q3: What’s the biggest benefit for cities?
Faster emergency response and better decision-making. Our findings show that response times drop dramatically when AI helps prioritize alerts.
Q4: Who should oversee these projects?
A mix of IT teams, law enforcement, and privacy officers. Through our trial and error, this cross-functional setup works best.
Q5: Can AI help prevent crime, not just detect it?
Absolutely. Predictive analytics and trend visualization help deploy police or resources proactively.
Q6: How do we handle false alerts?
By fine-tuning system thresholds and keeping human review in place. It’s all about balance.
Written by : Carlo Di Leo
At the age of 24, with no experience in the security industry or any money in the bank, Carlo quit his job and started Spotter Security from his parent's basement. Founded in 2004, Spotter grew from a single man operation into a multi-million dollar security system integrator that caters to businessess and construction sites across Canada.
