By Kevin Crothers

Published in T3 (Transport Technology Today), May 2008 

This year marks the 20th anniversary of the advent of mobile asset tracking systems, beginning with the introduction of OmniTRACS in 1988. We have come a long way from tools that reported the location of our trucks once every hour and allowed us to send basic text messages. In fact, now is a good time for us to ask how this technology will continue to evolve and what features and benefits can we expect in the future.

What was once mere automation of manual functions like driver check calls has now grown to full-featured systems that produce driver logs, compute fuel taxes, forward ECM fault codes and present other information about vehicle, driver and load. Systems are available that automatically record arrivals, departures and duration of stops, thus providing the raw information to support activity-based costing and much more.

The 20-year evolution has been significant. So what's next? Try automated event and status reporting with relation to geographic and business environments. This functionality will require more than just a GPS device tied to a cellular or satellite transceiver and a user access program featuring a map. It will require complex spatial and temporal rules.

What are spatial rules? They are a way to test for relationships among objects in their environment. These tests include conditions like: “is inside”, “within proximity of”, “in clusters of”, “exits”, “crosses”, and “intersects”. Spatio-temporal rules can also evaluate time constraints meaning certain rules only apply on weekends, during school hours, or between 6 and 11PM. These rules can be extended to include other business attributes like “if empty”, “if company driver”, or “if less than 8 driver log hours remaining”.

Why spatial rules? Three important reasons. The first is Automation.

Advances in location reporting technology are outpacing human ability to analyze the information. Today much of the location data that is collected goes unused. Meaningful insight may require complex evaluation, making timely analysis of the data impractical or impossible using manual techniques. Humans reason well and recognize patterns but are not good “monitors”. Knowing whether a truck has arrived on site is no longer good enough. Today's fleets want to know whether a truck is inside/outside the fence or even what dock door it is at. This takes complex capabilities such as concentric and irregular polygonic geofencing (e.g. the exact shape of the property or yard) in combination with a spatial rules engine to set up the event conditions and reporting requirements. The rules engine will then automatically sift and test the huge volumes of incoming data for the user-defined ruleset and report conditions requiring action.

The second reason is Time. From the moment location- and time-sensitive data is acquired, its value starts diminishing. The opportunity for extracting the data’s value may be as little as a few minutes. Monitoring spatio-temporal data on a 24 x 7 basis while scanning for numerous conditions is a considerable challenge, the success of which is directly tied to the ROI of the system. A spatial rules engine can monitor huge volumes of data by the second. When rules prove true notifications are “fired” to a queue, cell phone, email, report, pop-up window, etc. so that appropriate action can be taken immediately.

The third reason is Convergence. Asset location and attribute data often comes from multiple sources, e.g. separate power unit vs. trailer tracking systems or enterprise databases vs. EDI transactions, thus residing in “siloed” repositories. Performing cross-analysis and correlation on multiple data sources is difficult. Monitoring multiple data streams at the same time provides an opportunity to discover information and intelligence that might otherwise be missed. Addressing these challenges can have a real impact on the bottom line, whether through more efficient operations, risk reduction, enforcement of policies and standards, or perhaps even saving lives.

Consider the following problems that are best solved with spatial rules:

• Alert operations whenever 2 or more company trucks gather within 100 yards of each other at a non-business location for over 3 minutes.

• Locate the closest available dry van that hasn't moved in over 10 days, is at least 45' and is over 8 years old.

• Identify lower-cost options that occur when a moving truck is closer to a potential pickup instead of a preplanned truck further away.

• Record driver use of company vehicles outside business hours including weekends except to travel between a job site and home.

• Identify any out-of-route miles greater than 5% of the route, except in cases that run the driver by his/her home.

The knowledge of these scenarios is only of value if the reporting and monitoring are automatically determined and reported to the correct person or system so that driver notification is immediate and automatic. Only then will the value be harvested. An ounce of prevention is worth a pound of cure.

The systems of tomorrow will perform these functions. It is the next logical step. In fact, the systems of tomorrow are already being built.