#edge device

viMAC is viAct’s Edge AI solution for industrial vehicle safety, integrating AI-powered Anti-Collision Systems to protect forklifts, cranes, dump trucks, excavators, and tankers.

With on-device AI inferencing and on-premises processing, viMAC reduces near-miss incidents by up to 90%.

Key Integration Areas of viMAC include:

• Advanced Driver Assistance System (ADAS): Multi-camera, real-time alerts for safer vehicle-pedestrian and vehicle-vehicle interaction. • Proximity Warning & Anti-Collision System: Continuous monitoring to eliminate blind spots and enable instant intervention. • Danger Zone Alert Sensoring System (DZASS): Dynamic restricted zones with dual alarms for immediate hazard warnings. • Smart Site Safety System (4S): AI-powered enforcement of speed limits, seat belt use, and PPE compliance.

viMOV is the world’s first Mobile AI Monitoring Platform, purpose-built for extreme industrial environments. From remote locations to confined spaces and mobile workstations, viMOV ensures 78% faster emergency response, even without internet or power.

Here’s how it works:

• Real-Time Threat Detection: viMOV identifies safety risks instantly using AI-powered video analytics in movable cameras and IoT sensors. • Remote Alerts & Alarms: Integrated sound and light alarms with real-time notifications, it ensures swift action. • AI-Driven Insights: Proactive hazard mitigation through seamless AI analysis in monitoring atmospheric conditions, electric breaches and PPE compliance. • Centralized Safety Management: Unified platform offering real-time data and analytics in just a click for smarter, compliant site operations.

We're all laughing at Cisco, and their talk of 'fog computing.'

The name certainly invites ridicule but the underlying ideas - though not all new - have some merit.

Moving some compute closer to workloads at the edge of the network makes sense. For some jobs you want to amass data and throw brute force computing at it, backed by all the economies of scale inherent in a great big cloud. For others, a light-touch query of some subset of the data near its time and place of collection could be more efficient.

It makes sense to do some of this edge processing in intelligent network devices as Cisco (of course, given their core business) suggests. But it also makes sense to do a lot of it even closer to the edge; in the sensor itself.