No Battle Plan Survives Contact with the Enemy, Helmuth von Moltke
Optimizing transportation logistics is a key part of having an efficient supply chain system. Over the decades, vendors such as Oracle have developed sophisticated transportation management capabilities that help you with operational planning, transportation intelligence (tracking items, orders, or business metrics against forecasts), and fleet management (planning and utilizing fleet resources). To do such tasks, existing applications had to rely on data before the transit began (order, cargo, vehicle, driver, start time, source location) and the data collected at the end of the transit (end time, destination). This is fine if the journey is small, but usually, cargo travels for days and weeks. Events can happen that affect downstream supply chain partners.
As IoT becomes a sustainable platform component, we now have the advantage of using the real-time environmental conditions during the entire transit time to make more informed supply chain decisions. To address this, we developed the Oracle IoT Fleet Monitoring application.
In this blog, I’ll cover some of the key environmental conditions that the IoT Fleet Monitoring app captures, and how by combining that with contextual data sitting in other supply chain modules, we get the right insights AND develop a more adaptive supply chain system.
The IoT Fleet Monitoring app acquires a location by integrating with one of the sensors from our partners. These sensors could be OBDII dongles, J1939 telematics, or other sources that easily integrate with Oracle IoT Cloud Service.
With the IoT Fleet Monitoring app, you get real-time situational awareness of your
By tracking your fleet of vehicles in real time, you gain usable, decision-making information from your monitoring. The IoT Fleet Monitoring app can correlate contextual data such as cargo with the container in which it’s located. You’ll be able to provide your customers with order tracking information in real time.
Figure 1: Monitor your fleet at the level of your enterprise in real time.
Figure 2: IoT Fleet Monitoring computes the metrics based on the vehicles in your view.
By getting the location of the vehicle in real time, you can more accurately predict the estimated time of arrival (ETA).
The IoT Fleet Monitoring app is always evolving to collect subtle signals about vehicle performance. If a vehicle has a breakdown, then that has an effect on downstream work orders and supply chain components. It’s now possible to automatically notify your drivers and dispatchers about what’s happened, and simultaneously identify any resulting changes in the downstream supply chain plans. For example, say a vehicle isn’t operational and so it misses its scheduled delivery time. Don’t panic. You can cancel the current consignment order and immediately enter a new order into the supply chain system.
By tracking the vehicle condition in real time, you can avoid such drastic breakdowns because you can schedule regular repair and servicing. The IoT Fleet Monitoring app comes equipped with rules for tracking fuel, battery life, tire pressure, engine oil, RPMs, engine temperature, and geofences.
Figure 3: IoT Fleet Monitoring app provides a real-time view into the condition of the vehicle. In addition, with information from vehicle service records, the fleet manager can initiate the scheduling of servicing and reduce unplanned downtime.
Studies show that driver behavior affects vehicle wear and tear. Good driver behavior can improve the resale value of the vehicle as well as reduce the maintenance costs to repair and service it. According to the EPA, good driver behavior can enhance fuel efficiency by 33%. Good driving is like eating an apple – it keeps the doctor away. Good driving leads to a lower number of accidents and lower insurance premiums.
Figure 4: IoT Fleet Monitoring app provides powerful, ready-to-use rules to monitor driving behavior.
With the IoT Fleet Monitoring app, you as the fleet manager can activate supplied rules that relay information about drivers exceeding speed limits (alerts are sent when the driver goes too fast), hard braking or cornering, driving for too many hours in a row, or not following the prescribed route.