RIFE EDGE AI Vision System – On-Premise Video Analytics for Safety & Operations

RIFE EDGE AI • On-Premise Video Analytics Make existing cameras intelligent. RIFE EDGE AI adds a local computer-vision layer to compatible CCTV and IP camera networks for safety, security, asset visibility and operational monitoring. On-premise processing Existing-camera reuse Configurable AI applications System Concept One edge layer between your cameras and your response team The project is engineered around the camera network and the AI applications required at each zone. 01 INPUT CCTV / IP Cameras Compatible camera streams are validated for protocol, codec, resolution, frame rate, lighting and viewing angle. 02 EDGE Local AI Processing Selected video analytics run locally at the site on project-sized edge hardware. 03 DETECTION AI Application Library The project can use configured applications for people, objects, zones, hazards, access and operations. 04 ACTION Alerts & Workflows Detected events can support alerts, visual review and project-specific response workflows. Core Capability Stack Hardware + AI apps + site engineering RIFE EDGE AI is not a single fixed camera feature. The solution is configured as a complete site system around the buyer's required detections and existing infrastructure. Edge hardware Sized to camera channels and AI workload. AI applications Selected according to use case and camera view. Camera / VMS validation Compatibility verified during project design. Workflow integration Alert recipients and integrations defined per project. AI Application Library Configure only the detections your site needs PPE compliance Helmet, vest, gloves, eyewear where supported. Restricted-zone entry Virtual fences and defined areas. Line crossing Configured directional boundary events. Loitering Time-based presence in defined zones. People counting Camera-based counts where view is suitable. Queue & occupancy Operational visibility for selected areas. Fire / smoke / spill Visual hazard monitoring where applicable. Tool / object visibility Project-defined object and location workflows. Forklift safety Selected forklift and worker-safety events. Visual inspection Project-specific repetitive quality checks. Camera tamper Monitoring for selected camera-view changes. Access / tailgating Camera-visible events in controlled areas. Manufacturing Safety PPE, worker safety, forklifts, tools, zones and production-area events. Quality & Visual Inspection Evaluate repeatable visual inspection tasks where defect characteristics and camera views are suitable. Data Centre Security Restricted zones, access-area events, tailgating and camera-visible security workflows. Retail & Workplace Analytics People counting, queues, occupancy and selected space-usage monitoring. Deployment Architecture Designed around the site — not a generic box Camera count, AI workload, camera views, network design, storage requirements, integrations and alert workflows are assessed before the final edge hardware and licensing configuration is quoted. Single-zone or multi-zone projects Multi-camera and multi-site expansion Existing CCTV reuse where technically compatible Project-specific application selection Project Assessment Tell us the cameras. Tell us the problem. We map the EDGE AI configuration. For a project quotation, share your camera models, number of feeds, site locations, required detections, alert recipients and any VMS, ERP or workflow integration requirements. EDGE AI Vision System India A complete EDGE AI ecosystem for enterprise video analytics For Google and for buyers, the product is connected to RIFE's deeper technical and industry content so each major question has a dedicated answer. EDGE AI Vision Systems Overview of RIFE's on-premise AI vision platform and use cases. Architecture & Deployment How camera feeds, edge processing and deployment design fit together. Cameras, VMS & Integrations Compatibility and enterprise integration considerations. Privacy & Cybersecurity Data control, privacy and cybersecurity considerations for enterprise deployment. Accuracy, Testing & Validation Why site conditions and validation matter for computer-vision projects. EDGE AI Appliances & Hardware Hardware sizing and deployment considerations for camera workloads. Industry Solutions Explore EDGE AI by operating environment Manufacturing Worker safety, tool tracking and production visibility. Data Centres Physical security, access monitoring and asset visibility. Healthcare Selected safety, occupancy and operational monitoring use cases. Retail People counting, queues, occupancy and selected security workflows. Schools & Campuses Campus safety, zones and selected security applications. Logistics & Warehouses Safety, restricted zones, people and asset-related workflows. BUYING GUIDE Safety & PPE Monitoring Guide Understand camera positioning, site conditions, detection goals and deployment planning before choosing an AI vision system. Read the EDGE AI buying guide → PILOT Start with a focused pilot A pilot can validate camera views, operating conditions and selected detections before a wider rollout. View the RIFE EDGE AI pilot program → TECHNICAL FAQ Deployment & Support Review common questions about deployment, integration, support and technical planning. Read the technical FAQ → Frequently Asked Questions RIFE EDGE AI Vision System FAQs Can RIFE EDGE AI work with existing CCTV or IP cameras? Potentially, yes. Camera reuse depends on technical compatibility, including protocol, codec, resolution, frame rate, lighting, viewing angle, network capacity and the detection task. RIFE validates the camera environment during project design. Is RIFE EDGE AI cloud-based or on-premise? The core deployment described on this page is based on local edge / on-premise video analytics. The final architecture is defined according to the buyer's project requirements. What can an EDGE AI vision system detect? Applications can be configured for selected tasks such as PPE compliance, restricted-zone entry, line crossing, loitering, people counting, queue and occupancy monitoring, camera tamper, visual hazards, tool or object visibility and other supported computer-vision workflows. Can the system be used for manufacturing safety? Yes. Manufacturing projects can be designed around camera-visible safety and operational use cases such as PPE monitoring, forklift-area safety, restricted zones, tool visibility, selected hazards and visual inspection tasks. How is the edge hardware selected? Hardware sizing depends on camera-channel count, video characteristics, AI workload, site architecture, storage requirements and the applications required. It should be engineered for the project rather than selected as a generic fixed box. Can RIFE EDGE AI be deployed at multiple locations? Projects can be planned for focused zones, multiple cameras or broader multi-site deployments. The final architecture depends on the number of locations and the required workflows. Does every project require the same AI applications? No. The application mix is selected according to the operational objective, camera view and site conditions. A factory, data centre, hospital and retail site will normally require different configurations. What information should we provide for a quotation? Share the site type, camera models, number of feeds, locations, required detections, alert recipients and any VMS, ERP or workflow integration requirements. This allows RIFE to map the appropriate deployment architecture before quotation. Industry AI buying guides Move from a use case to procurement criteria, compatibility, validation and pilot planning. Healthcare Buyer Guide →Manufacturing Buyer Guide →Schools Buyer Guide →Data Centers Buyer Guide →Warehousing Buyer Guide →Retail Buyer Guide →Hotels Buyer Guide →Corporate Offices Buyer Guide →Construction Buyer Guide →Property Management Buyer Guide →Banking Buyer Guide →Corporate IT Parks Buyer Guide →