Fleet Mobility – Alphabet Soup
We may feel the same about the terms floating around the transportation industry to explain mobility technology. Some of these terms are defined below.
- AI (Artificial Intelligence) – The development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages (Oxford Language dictionary via Google)
- ELD (Electronic Logging Device) – An ELD synchronizes with a vehicle engine to automatically record driving time, for easier, more accurate hours of service (HOS) recording. (US Federal Motor Carrier Safety Administration at fmcsa.dot.gov/)
- Geofencing – The use of GPS or RFID technology to create a virtual geographic boundary, enabling software to trigger a response when a mobile device enters or leaves a particular area (Oxford Language dictionary via Google)
- GPS (Global Positioning System) – a navigational system using satellite signals to fix the location of a radio receiver on or above the earth’s surface (https://www.merriam-webster.com)
- RFID (Radio-Frequency IDentification) – Technology that uses radio waves to read and collect information from a label/tag (https://internetofthingsagenda.techtarget.com/)
- Machine Learning – The process by which a computer is able to improve its own performance by continuously incorporating new data into an existing statistical model (https://www.merriam-webster.com) without explicit programming. Machine learning helps a computer to achieve artificial intelligence. (https://www.britannica.com)
- Telematics – The use of wireless devices and “black box” technologies to collect and transmit data in real time back to an organization (https://www.gartner.com/en/)
What do they have in common besides giving you a full spoonful of alphabet soup? The answer is Fleet Management software is dependent on these tools to collect and process the data required to manage a fleet’s resource (equipment & driver) performance, safety, freight regulation compliance, and fleet equipment maintenance. Just as you can construct words from the letters in alphabet soup, you can combine these technologies to play a significant role in best of class Fleet Management, for example:
- Driving routes setup with geofencing enabled for each shipment.
- Workers attach RFID tags containing finished product and related details before shipping.
- Drivers scan the RFID labels on the products, containers or pallets and load them onto outbound trucks.
- ELDs record when trucks leave the shipping location, their speed, idle time, etc.
- Telematics transmit ELD data back to the shipper’s host system and continue to do so until the route is completed.
- If a driver deviates from the expected route, Geofencing is triggered. By using the RFID tag or GPS on the tractor, an alert is sent back to the shipper.
- Driver scans the shipment’s RFID labels at all stops including the final destination to complete the deliveries.
- Driver returns to the shipper location.
- Once a route is completed, Machine Learning processes the recorded data and performs analyses to determine and implement the changes needed to improve performance.
- IT uses the data from the above to develop AI to imitate informed human behavior
Now that I am older and somewhat wiser, a bowl of alphabet soup is no longer intimidating (except for the taste, but that is a different subject). After reading this blog, I hope you feel the same about some of the mobility technology required to enable a fleet management system that delivers the results you need!
Stay tuned for more blogs that continue to explore the transportation industry and its systems.
–Jess Kittrell, St. Onge Company
