Sprinx // co.exist

Video-based smart solution for people & vehicle mobility analysis

Combining artificial intelligence and a user-friendly interface, co.exist offers people counting and traffic event detection in smart cities and public areas.

Exploiting the powerful neural network, co.exist is the Sprinx solution dedicated to multimodal mobility in city, logistics and transport sectors, able to analyze video streams in real-time, track objects in the scene, quickly identify any anomalous situations and collect statistical data related to mobility.b

co.exist in the server-side solution is completely agnostic to the camera brand, requiring for analysis simply a standard Onvif-RTSP stream. 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. co.exist transforms even existing cameras, installed for purely video surveillance purposes, into intelligent sensors for mobility analysis.

How it works

Using Intel® OpenVINO™ toolkit, 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 as well as being equipped with its front-end can be easily integrated into more complex system architectures, public and private, through the activation of standard communication protocols (example: HTTP, TCP in Json format, FTP, ModBus , OPC UA, OPC DA) or custom ones.

The use of neural networks trained for behavior analysis applications, integrated with a 3D object tracking approach, allows being particularly adaptive in pre-existing CCTV systems ensuring good performance even in not optimal installation and environmental conditions.

Co.exist is a social distancing sotware developed by Sprinx.ai

Dragon for co.exist

Event manager

co.exist can quickly alert operators in case of accidents, traffic slowdowns or gatherings, sending event notifications, as well as to the centralized management platform Sprinx dragon, to third-party systems (eg VMS, SCADA or ITS platform) capable of triggering scenarios of visualization and intervention.

Co.exist is a social distancing software that helps to avoid crowded areas

Dragon for co.exist

Data Collection

co.exist also collects statistical data relating to multimodal traffic (people, vehicles, soft mobility), allowing to enhance the role of video surveillance cameras by attributing them functions typically delegated to other technologies /sensors.

With Multi-camera tracking module

Video Analysis
R-Evolution

Thanks to the integrated Multi-camera tracking module, co.exist enhances safety and security by analyzing the behavior of people and vehicles in their entire movement while in view of cameras.

Key Features

Field Proven AI

More than 15.000 cameras around the world turned into intelligent sensors by Sprinx software since 2009

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.

Plug&Play

Fast Calibration and Easy Configuration, ready to interact with third-party CCTV & mobility platform

Adaptive & Cost Effective

Decision-making tool for a smarter mobility, compatible even with existing CCTV cameras

On board Camera

Installable directly onboard the Open Platform video cameras major CCTV manufacturers on the market

CPU only

The AI inference engine based on Intel OpenVINO does not require any additional hardware or GPU

Traffic Event Detection

Vehicle Counting & Classification

People Counting

Origin/Destination Matrix

Traffic Data Collection

Counting of people, bicycles, and vehicles in transit;
Origin/destination matrix at intersections/roundabouts
Classification of vehicles in transit (4 classes: motorcycle, car, van/commercial vehicle, truck/bus)
Average speed of vehicles divided by vehicle class (km/h per class)
Traffic density, calculated on the basis of the integration of multiple data

Application Field

Smart Cities

Transportation

Logistics

Video-based smart solution for people & vehicle mobility analysis

Smart City

Ente Autonomo Volturno

San Giovanni Hospital