IoT condition-based monitoring and AI predictive maintenance track asset location, health and lifecycle to cut downtime and extend asset life across industries.
Siloed systems, outdated CMMS platforms and reactive maintenance leave organisations with unplanned downtime, asset loss and limited real-time visibility of critical infrastructure.
365mesh Asset Management pairs IoT condition-based monitoring with AI predictive analytics to track assets in real time and shift teams from reactive fixes to proactive, data-driven maintenance.
IoT sensors on machinery, vehicles and infrastructure capture condition and location data; telemetry flows natively into the 365mesh platform via a unified API; AI and machine-learning models detect anomalies and forecast failures; and teams receive automated alerts and lifecycle insights.
Vendor documentation: link 1 · vendor website
Evidence level: L2 · Documented: how evidence levels work
Continuous visibility into asset location, condition and usage across fixed and mobile assets.
IoT sensors for vibration, pressure, temperature and oil analysis monitor machinery, vehicle and asset health.
Machine-learning models forecast maintenance needs from usage, wear and environmental data to prevent failures.
Assets are tracked from acquisition through maintenance to decommissioning for optimised replacement planning.
Spatial tracking and dynamic visual overlays enrich asset data with location-aware and predictive context.
A full event history per asset supports auditability, regulatory compliance and insurance verification.
Ask the AI Solution Architect: compare this solution against alternatives, check connectivity for your region, and get integration guidance. Included with IoT Apps Enterprise.
Fit, availability or a detail on this page. Goes straight to 365mesh, no RFP needed.
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