Intelligent Lawn Mow Routing using Automatic Vehicle Locator Technology for Smart City

In Winnipeg, MB, grass and weed growth can be seen during the summer, up until the middle of October. Weeds such as dandelions are hazardous to human health as they can trigger allergic and asthmatic reactions to the public. Their roots can grow up to two feet long if not removed on time. During the grass growth period, the City of Winnipeg uses many mowers of different sizes and horse-powers to mow and remove the weeds in boulevards, athletic fields, parks and other city owned green spaces. Currently, mowing routes are decided manually by the foremen. This is inefficient and time consuming. In the past year, the City has initiated a pilot Smart City mowing tracking project using Automatic Vehicle Locator (AVL) technology. These devices have been installed on lawn mowers and the City has been gathering data such as the geographical locations and speeds of the vehicles. We propose to use the AVL data to automate routing in real-time. We will synthesize an efficient routing algorithm that minimizes the transportation cost of the different lawn mowers by finding the shortest path between mowing location.

Faculty Supervisor:

Parimala Thulasiraman


Zhuoran Sun


City of Winnipeg


Computer science




University of Manitoba



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