[ INSIGHT ] SCVISIBILITY by Eric Wambua (left) Chief Financial Officer, Edgetrack Solutions LLC eric.wambua@edgetrack.io | 859-436-3193 and Shem Odhiambo
Chief Executive Officer, Edgetrack Solutions LLC shem.odhiambo@edgetrack.io | 859-539-0356
Seeing Around the Next Bend Global supply networks involve many partners and recent shocks have shown how quickly a single disruption can ripple through the system. Traditional visibility stitched together data from transportation, warehouse, and enterprise systems and augmented it with GPS or RFID tags; those tools provide only snapshots of past movements.
management, warehouse and enterprise systems, GPS devices, RFID tags, camera feeds and external services. Standardizing data formats ensures analytics operate on accurate inputs and gives all partners a shared view of reality. 2. Instrument the chain with sensors and cameras. Use telematics sensors to capture location and environmental conditions, and deploy AI‑enabled cameras for road and driver awareness and to verify equipment. 3. Apply advanced analytics and decision automation. AI pipelines connect to multiple platforms and IoT devices, enabling continuous monitoring and predictive alerts. Integrated with operational systems, these models can automatically assign docks, trigger maintenance or reroute drivers. 4. Collaborate and develop skills. Visibility delivers value only when partners share data and employees act on insights. Establish data‑sharing agreements with suppliers and carriers, maintain system interoperability and train teams to interpret dashboards and respond quickly. End‑to‑end visibility enables a supply chain that can adapt to disruptions, operate efficiently and deliver on environmental commitments. Businesses that invest in data integration, AI analytics and collaborative workflows today will be better prepared to navigate the uncertainties of tomorrow.
gate readers instantly identify equipment and update statuses, cutting dwell time. Visibility now depends on more than GPS coordinates. Vehicles equipped with computer‑vision modules scan the road ahead, and detect potholes, debris or lane blockages that could slow or damage a load. These observations feed into routing engines that also ingest traffic speeds from digital maps and crowd‑sourced congestion feeds. Dynamic route optimization platforms combine GPS, congestion and weather data to anticipate delays and reroute vehicles. Predictive models integrate seasonal patterns to forecast demand and align production with expected orders. Monitoring road and traffic conditions helps avoid hotspots, supports sustainability goals and improves on-time performance. Achieving adaptive control is a transformation built on four pillars: 1. Centralize and clean data. A cloud‑based control tower should ingest live streams from transportation
In an era of intelligent logistics, the goal is continuous situational awareness. Modern tracking integrates analytics and AI camera modules into vehicles to detect road and driver conditions, pulls live traffic data from digital maps, and automatically reroutes shipments when congestion or hazards arise. FROM PASSIVE DATA TO ACTIVE INSIGHT Next‑generation tracking platforms ingest data from telematics devices, IoT sensors, and AI‑enabled cameras and combine it with external variables such as weather. Machine‑learning models turn that torrent into foresight. AI systems can analyze traffic patterns, road closures, weather, and delivery priorities to suggest the fastest routes in real time. Instead of waiting for end‑of‑day reports, predictive algorithms flag slowing shipment velocity or supplier issues and recommend actions before problems spread. Driver‑monitoring cameras can detect fatigue or distraction and trigger alerts. In yards, automated cameras and
80 Inbound Logistics • January 2026
Powered by FlippingBook