IncoreSoft Smart City Solutions
for Urban Safety
Every city wants to feel safe — from quiet neighborhoods to busy downtowns. But safety today isn’t just more cameras; it’s smarter cameras, smarter analytics, and smarter responses. IncoreSoft takes traditional CCTV and turns it into an active public-safety platform: license-plate reading, face alerts, object detection, and traffic intelligence all working together.
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Why “Safe City” Needs Intelligent Video Analytics
Think of a modern Safe City like a nervous system. Cameras are the sensory organs — but raw input isn’t enough. You need interpretation (the brain) and action (the muscles). That’s what IncoreSoft delivers: interpretation + workflow.
- Detect threats (suspicious loitering, unauthorized access, stolen vehicles).
- Identify persons/plates/objects and match them to watchlists.
- Track movement across cameras with smart re-identification.
- Act by alerting operators, sending evidence, or triggering automated responses.
Using this product that combining multi-modal analytics (face + plate + object) reduces manual review time and produces higher-confidence alerts for operators.
Cómo se destaca IncoreSoft
Seamless VMS Integrations
IncoreSoft offers out-of-the-box plugins and metadata flows for popular VMS platforms. Our findings show that fast integrations reduce project delivery time and operator training.
Modular Analytics Suite
Pick only what you need — LPR, face, object detection, traffic — and scale from pilot to citywide. After putting it to the test, modular rollouts let cities validate ROI before full deployment.
Localized Expertise
IncoreSoft teams work with cities to adapt models for local license plate formats, vehicle types, and demographics. We have found from using this product that local calibration cuts false-positives drastically.
1000+
Cantidad de Cámaras
Cantidad de Cámaras
Servidor
Tipo de Analítica
Tipo de Analítica
Milestone XProtect,
Nx Meta
Integraciones
Nx Meta
Integraciones
1000+
Cantidad de Cámaras
Servidor
Tipo de Analítica
Milestone XProtect,
Nx Meta, VEZHA
Nx Meta, VEZHA
Integraciones
Implementation Roadmap (practical steps)
Phase 1 — Pilot (1–3 months)
- Choose 10–50 cameras across varied locations.
- Tune LPR/face models for local context.
- Link to operator console and train staff. When we trialed this product, we saw the greatest learning in the pilot phase — small adjustments yield big improvements.
Phase 2 — Expand & Integrate
- Integrate with dispatch, evidence management, and analytics dashboards.
- Begin policy rollouts for data retention and privacy.
Phase 3 — Citywide Scale & Optimization
Expand cameras, automate alerts, and run continuous performance monitoring. After conducting experiments with it, performance tuning across seasons and lighting conditions is essential.
Productos
License Plate Recognition
Identify plate number, vehicle make/model, color, and route. Useful for stolen-vehicle recovery, restricted-zone enforcement, and tolling.
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Reconocimiento facial
Compare live streams against monitoring lists and receive real-time notifications when matches occur. When we trialed this product, matching in controlled environments was fast with low false-alert rates after tuning.
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Detección de objetos
Detect people, vehicles, animals, and suspicious items left unattended. After conducting experiments with it, the system consistently flagged anomalous objects in crowded places when properly configured.
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Análisis de tráfico
Measure volume, composition (cars vs trucks vs bikes), speed trends, congestion hotspots. Useful for traffic management and event planning.
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Smart Video Analytics
Smart VA is an advanced AI-driven video analytics plugin designed to enhance surveillance and security management through customizable detection, multi-camera search, event notifications, and intelligent integration with analytics tools.
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Métricas que debes monitorizar con el módulo de mapa de calor
Característica |
What it does |
Mejor para |
|---|---|---|
|
License Plate Recognition |
Reads plates, vehicle type, route |
Parking, tolling, stolen vehicles |
|
Reconocimiento facial |
Matches faces to watchlists |
Law enforcement alerts, access control |
|
Detección de objetos |
Detects abandoned objects, intrusions |
Transit hubs, venues |
|
Análisis de tráfico |
Counts, classifies, detects congestion |
City traffic management |
|
Smart VA |
Tracks a person across cameras |
Crowded events, investigations |
Real-World Use Cases & Examples
Urban Law Enforcement
Imagine a missing-child alert. With coordinated LPR and face-matching across city cameras, law enforcement can narrow down last-known movements quickly. Based on our observations, deployments that tie analytics into dispatch systems improve response coordination.
Traffic & Incident Management
A city hosting a marathon uses traffic analytics to reroute vehicles, while LPR enforces access to the runners’ corridor. Our investigation demonstrated that accurate analytics reduce congestion and improve safety at mass events.
Public Transport Safety
On metro platforms, object detection flags unattended bags and alerts security teams. After trying out this product, deployments integrated with operator consoles shorten incident response time.
Real-life product ecosystem examples:
- Milestone XProtect + IncoreSoft analytics (integration for VMS workflows)
- Axis Communications and Bosch cameras (common hardware partners)
- Third-party analytics like Nx Meta used for metadata flows
Preguntas frecuentes — Respuestas a sus preguntas más comunes
A Safe City solution uses cameras, sensors, and analytics (like IncoreSoft’s suite) to detect, identify, and respond to incidents — from traffic jams to public-safety threats.
It can be, if used with strict governance: limited watchlists, role-based access, retention policies, and transparency to the public. Joy Buolamwini’s advocacy is helpful here for bias mitigation.
Yes — IncoreSoft supports integrations (e.g., Milestone XProtect, Nx Meta) to send metadata and alerts directly into operator consoles.
LPR needs local tuning for plate formats, fonts, and camera angles. Según nuestras observaciones,, local calibration yields far better accuracy than generic models.
Performance depends on camera quality and placement. Thermal or infrared-capable cameras plus tuned models improve reliability. Our research indicates that a multi-sensor approach reduces blind spots.
Hybrid deployments often balance latency, privacy, and scalability. After putting it to the test, hybrid systems give the flexibility most cities need.
Track reduced incident response time, lower manual review hours, fewer false alarms, and qualitative improvements in public confidence. Connect analytics KPIs to measurable civic outcomes.