The data is then fed to Scentroid’s odour prediction algorithm which uses deep learning technology to map the sensor data to numerous SM100i field olfactometery readings to determine the odour concentration in OU/m3. Additional Scentinal SL50s are placed for direct emission measurements of high odorous sources such as aeration tanks, Inlet works, and sludge dewatering. The SL50s have the same built-in deep learning algorithm that will calculate the odour concentration of the gases being emitted.
All data is sent to Scentroid’s Total Odour Management System (TOM) which utilizes fuzzy logic algorithms to continuously update a live air dispersion model. Metro Vancouver can now not only detect changes to process emissions instantaneously but also verify complaints, predict odour episodes and even optimize process variables to achieve minimal odour impact.