1. [Home](https://muga.uz/en/) 2. Platform Platform # MU Platform One platform instead of a patchwork of systems [Discuss your project](https://muga.uz/en/contacts/) [Request a presentation](mailto:info@muga.uz?subject=Presentation%20request%3A%20Platform) ## What the platform brings together MU Platform brings video surveillance, video analytics, biometrics, access control, transport, mobile sources and IoT together in a single monitoring and management environment. The platform is vendor-independent: it connects equipment and analytics from different suppliers through a single API, scales with your infrastructure and runs wherever you need it – on your servers, in the cloud or in a hybrid setup. The platform connects to existing cameras over standard protocols and does not interfere with the existing video surveillance system. ## Modules ### Video analytics Event detection on existing cameras: people and vehicles, dangerous situations, violations of regulations. Missing detectors are developed for the customer's task. ### Biometrics and access Face-based access with liveness and deepfake detection, integration with existing access control systems, access events and video in a single console. ### Industrial safety PPE by role and area, hazardous areas with several criticality levels, staff behavior, fire and smoke, thermal imaging monitoring of equipment overheating. ### City infrastructure The foundation of a situation center: fixed and mobile sources on one map, monitoring of street maintenance, public amenities and the environment, objective oversight of contractors. ### Video management (VMS) Cameras from different manufacturers, camera map, role-based access, browser viewing, recording to file and S3 storage, API. ### API and integrations A single API for equipment and analytics from different suppliers; event exchange with process control systems, SCADA, access control, ERP and PSIM. ## Video quality monitoring – the base layer Without quality monitoring, analytics runs on unusable data. The platform automatically finds cameras that are formally working but deliver an unusable picture: - dirt, defocus, condensation, glare; - shifted or blocked view, no signal; - sensor defects, wrong time and overlays; - a PTZ camera drifting from its home position. Checks run in day and night modes and compare the picture with a reference scene. Covering, shifting, defocusing or disconnecting a camera is logged as an event – protection against sabotage. The same layer makes it possible to oversee contractors who maintain the cameras and replaces manual audits with site visits. ## Incident cycle Detection → event → operator confirmation → incident → routing by role → follow-up → reports and prevention of repeat incidents. Evidence is kept for every incident: a snapshot and video clip, an archive with metadata, a before-and-after comparison. Alerts are sent to Telegram and by email according to configurable rules. ## Human in the loop The system detects and prioritizes; a responsible person makes the decision. This reduces the flow of false alarms. - Models are fine-tuned on data from the specific site: every operator confirmation or rejection improves the model. - The model's confidence threshold is configured to match the customer's regulations. - By default, there is no personal identification: a violation is linked to an area, a camera and a time. Employee recognition is a separate stage, at the customer's discretion. ## Deployment ### Within the customer's perimeter On the customer's servers, in the cloud or in a hybrid setup. Data stays within the customer's perimeter. ### Distributed sites Local nodes keep working autonomously if the connection drops. Events go to the situation center; video is sent on request. From remote sites, video is transmitted over mobile networks with multi-SIM bonding, failover and encryption. ### Intelligent video archive AI analysis of recorded video: event search, incident review, flow analysis without real-time equipment. Scenarios are first tested on the archive; only confirmed ones are switched to real time. ## Integrations SCADA, process control systems, PLC (OPC UA, Modbus TCP), REST API, access control systems, ERP, PSIM. An AI assistant for video analytics data answers questions in natural language: a shift summary, an occupational safety report, anomalies. The language model runs within the company's perimeter, read-only and within the user's permissions, and is not tied to a single language model. - SCADA - Process control systems - PLC (OPC UA, Modbus TCP) - REST API - ACS - ERP - PSIM ## Related solutions - [Platform industrial module](https://muga.uz/en/platform/industrial-module/) How we work 1. ### Defining the task We analyze the customer's process and define scenarios and control points. 2. ### Pilot We run the scenario on real data and existing infrastructure. 3. ### Full-scale operation We scale the solution and connect related systems. 4. ### Development and support We update modules, add scenarios and provide ongoing support. Engagement models: turnkey project, module licensing, subscription, service model. Contact ## Discuss your project We will send you a presentation of any solution you are interested in. [Discuss your project](https://muga.uz/en/contacts/) [Request a presentation](mailto:info@muga.uz?subject=Presentation%20request%3A%20Platform) Phone [+998 94 830 60 75](tel:+998948306075) E-mail [info@muga.uz](mailto:info@muga.uz) Address 25 Amir Temur Avenue, Tashkent Office hours Mon–Fri 9:00–18:00 (UTC+5)