While the picture here looks like a truck swallowing its cleaner, this is from Townsville where they’ve recently had lots of flooding from un-seasonally heavy rains, so all efforts are made to improve truck hygiene while reducing any ponding-water and minimise risk of attracting “the big mozzie” during a dengue virus outbreak in this tropical area.
ASPsoftware has recently been working with Townsville’s Waste Services (TWS) department to help balance driver workloads (another source of ‘health risk’ for overworked drivers and trucks). After merging two neighbouring cities residential collection areas, TWS engaged ASP to help by computerising their yellow-highlighted paper-map route-plans and gather onboard data to facilitate a fairer distribution of workload amongst runs in any day of service area.
The solution involved innovative use of councils cadastral map data linked to data from new onboard GPS devices that could also automatically capture each side-lift arm movement. The solution ASP developed was able to count the actual lifts against potential properties in any marked out run area boundaries on the map as well as compare the potential distance in these areas with that actually travelled (both inside run boundaries and in transit to and from the depot or tip).
The next step once raw data started to emerge showing large workload discrepancies, was to have the computer split the day of service area for multiple
trucks into smaller parcels of bins so that software system could recommend where to move or re-partition individual truck route boundaries within a selected day of service area, to come up with a more even workload.
While this is not rocket science to a mapping guru, in layman’s terms it does involve calculating how long it’s likely to take to do a street side section based on an expected average travel speed and allowing a set number of seconds per lift stop point. The idea is that different streets have different densities of residents (no pun intended) so to do a reasonable balancing job of time and distance factors for different population density areas the computer can do the math in a few minutes. Add to this some factors such as when the truck is likely to be full (assuming an average bin volume or weight) and the computer can project where best to break and go to the nearest tip.
In a normal residential collection cycle, each day-of-service area may move the
trucks further away from the depot and further or closer to different disposal points. Test-driving suggested changes will then bring-back any unexpected actual time-of-day traffic or terrain variations. This gives you feedback on how close the projected balancing factors were to the real life run time and lift counts. For good measure, time allowances were added for driver fatigue rests and lunch breaks as well as that hygienic truck wash at end of day.
The end objective: less stress and wear and tear on drivers and trucks, from automated data capture and a clearer picture of presentation rates that in-turn will lead to encouraging more recycling.