Fleet Management. The veteran of IoT solutions

Published by Telefónica IoT Team Smart Mobility

Fleet Management is one of the few long established IoT solutions. Computerized asset management goes as far back as the early years of non-military computing in the 1950s. The emergence of the Internet added primitive online telematics some 25 years ago. The reasons behind the sustained success of these solutions is that technology worked very clearly in favor of automation and adding obvious advantages:

  • Fleet Management improves the control of costly assets
  • A progressive drop in connectivity costs improves adoption rates
  • Knowing the precise location of assets allows to make real-time decisions
  • Any optimization deeply impacts on optimizing business processes and cutting costs, achieving an overall efficiency improvement
  • The drop in connectivity and chip costs has made it possible for businesses of all sizes to add telematics to vehicles, containers and other devices

IoT is a natural evolution of other preexisting connectivity technologies that bring devices together. In fleet management in particular, and in telematics in general, m2m connections has been one of the most frequent methods to connect assets to a management system.  IoT as an evolution of m2m connections, takes into consideration not only the device to device connectivity but also the use of data.

The Internet of Things has made it possible to use Fleet Management practically everywhere: from trailer trucks, to trains or even airplanes. End users can benefit from B2B2C uses that surpass the initial B2B scope fleet management had. Thus, taxi fleets, rent-a-car companies, or courier companies can offer new services to customers thanks to this tracking. Smart Cities also greatly benefit from connected fleet services and use telematics to manage waste disposal vehicles or city police cars.

When managing vehicle telematics data there are two distinct application fields: vehicles and data regarding the drivers in order to help them perform their job better.

We will refer to a fleet of connected trailer trucks to illustrate. At the vehicle level we can manage assets such as:

  • Operating time (uptime) for the vehicle, which should be maxed out
  • Downtime due to vehicle maintenance
  • Time / Kilometres a replaceable part has been in use
  • Time the vehicle is idle
  • Status of parts in real time through sensors

We can also manage our human resources thanks to fleet management systems:

  • Coach drivers in real time to help them optimise the best way of accelerating, braking and managing gears for fuel efficiency
  • Ensure that drivers are rested
  • Ensure that routes are optimized

We will thus be able to cross reference data that will tell us which vehicles operate better on which routes, which drivers adapt better to which vehicles, etc. And since we already know the routes our vehicles will follow and the wear of the parts, we will be able to prepare spare parts at the next destination point and avoid unnecessary downtime.

The amount of collected data increases as the complexity of the managed processes grows  (almost 5 Mb / km for each vehicle, estimates Intel). We will not want (nor be able) to transfer all the collected data to the collection point. Therefore vehicles do not only transfer data, but also process and even store data at the vehicle level (mostly collected by sensors). On board management will process part of the collected information – that may or may not be stored – and transfer another portion to a fleet data collection point.

Even though fleet management is one of the most primitive applications of computing, it has adapted to changing times and has been able to maximize the availability of the Internet, and the drop in connectivity prices. It has also been successful in transitioning between m2m point to point connections to more complex scenarios in order to maximize IoT strengths, relying on Cloud Computing (and its sibling Fog Computing), Big Data, and Machine Learning.

Telefónica IoT Team