Video-based smart solution for people & vehicle mobility analysis

Exploiting the powerful neural network, co.exist is the Sprinx solution dedicated to multimodal mobility analysis in the city, logistics, transport and public sectors.

co.exist can analyze video streams in real-time, track objects in the scene, quickly identify anomalous situations, and collect statistical data related to mobility of people and vehicles.

co.exist is a sustainable solution, transforming even existing standard CCTV cameras, installed for purely video surveillance purposes, into intelligent sensors for mobility analysis.

co.exist is a solution flexible, scalable, adaptive and sustainable, which allows the optimisation of investments and the reduction of the environmental impact.

How it works

Sprinx as an Independent Software Vendor (ISV) is focused on developing software platforms that can be installed, both server-side and at-the-edge, on market hardware and belonging to different brands.

co.exist combines Artificial Intelligence algorithms, a user-friendly interface and Data Intelligence to monitor people and vehicle mobility by generating alarms and statistical data without installing additional equipment. The software platform, equipped with its front-end, can be easily integrated into more complex system architectures, public and private, through the activation of standard communication protocols or custom ones.

co.exist in the server-side solution, using Intel® OpenVINO™ toolkit,  is entirely agnostic to the camera brand, requiring simply a standard Onvif-RTSP stream for analysis.  As for the at-the-edge solutions, Sprinx has been undertaking a verification activity for some time now, aimed at selecting and certifying devices capable of guaranteeing performance levels according to Sprinx standards.

Activating professional algorithms directly onboard the camera represents an extremely interesting and cost-effective solution in distributed architectures, such as urban ones. Moreover, onboard analytics allow not worrying about the network infrastructure.
Using for the analysis of the Raw image coming directly from the processor also allows to keep the camera performance constant, not even decreasing the flows and profiles available on the camera.

The use of neural networks trained for behaviour analysis applications, integrated with a 3D object tracking approach, allows being particularly adaptive in pre-existing CCTV systems ensuring good performance even in unsuitable installation and environmental conditions.

Additionally, the co.exist  web user interface displays a dashboard and an event journal for tuning and maintenance purposes. Mobility data and alarms can be forwarded to third-party systems using standard protocols and displayed on the Sprinx centralized management platform, dragon.

Key Features
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Field Proven AI
More than 15.000 cameras around the world turned into intelligent sensors by Sprinx software since 2009
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Hardware Agnostic
Compatible with any IP camera or video encoder that supports RTSP video streaming protocol. This scheme facilitates system maintainability while enabling limitless evolution
Mobility Insight
Centralized upper-level user experience empowered by Dragon.
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Plug&Play
Fast Calibration and Easy Configuration, ready to interact with third-party CCTV & mobility platform
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Adaptive & Cost Effective
Decision-making tool for a smarter mobility, compatible even with existing CCTV cameras
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On board Camera
Installable directly onboard the Open Platform video cameras major CCTV manufacturers on the market
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CPU only
The AI inference engine based on Intel OpenVINO does not require any additional hardware or GPU
Application Field
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Smart Cities
Transportation
Logistics