Together with Capgemini, Blue Yonder is enlightening the world by demonstrating the potential of connected services by making streetlights intelligent. Through the use of LED streetlights, cities and towns are able to reduce their total costs of lighting up the night.
In the last four weeks of its life, a streetlight becomes inefficient, requiring the most energy to run and is in need of replacement. Without a doubt, street lighting is an expensive commodity and accounts for between 30%-50% of all energy usage within a town or city. Before now, it was not possible to accurately predict the end of life of a street lamp, meaning that corrective action often came too late.
To overcome this issue, Blue Yonder has been working with the Consultancy Capgemini as part of a pilot project to make lighting “intelligent”. Lights with sensors can provide data on their condition, including: information on vibration, the intensity of light being emitted, and also energy efficiency. Based on data collected from thousands of light sensors, a predictive application based on the Blue Yonder platform can calculate the probability of a light going out and when this is most likely to occur.
The automation of decisions is the decisive outcome of every Predictive Application. Just being able to read and interpret the data is no longer the only desired outcome, it all comes down to being able to gain insight in order to create actionable decisions which drive positive changes. In the case of connected services, this means that cases are automatically created for each event, regardless of whether it has occurred or will occur at a later time.
This new technology can provide considerable advantages when it comes to maintenance: Routes can be optimized when the software determines that on a certain street at a certain time multiple lights are about to go out. By evaluating the temperature of the lights through the software, the service personnel can act before a set energy limit is reached. A particularly high amount of power is wasted as the light burns out. Those times can also be predicted and avoided. Just the right moment must be chosen. For example, if 200 lights are replaced a week too early, 200 light weeks are wasted. Predictive applications and their accurate forecasts enable costs to be minimized. In addition, various indicators make it possible to locally prevent vandalism.
A pilot project for service Automation
Because the amortization cycles of capital goods like lights are very long, intelligent lights pay off, because they drastically lower the total cost of ownership. The pilot project goal was to use streetlights to demonstarte the potential of service automation. In comparison to a car, where 2,000 parameters are captured and analyzed second-by-second, a light is an easy to capture data object.
In this case, cost savings and high levels of service demonstrate —the potential advantages of connected services for the consumer segment. For example, an adapted predictive application can accurately determine the maintenance needs, the driving style for insurance pricing, and the accident risk for a vehicle. We are taking the first steps on the way to a connected world and are looking forward to the challenges as well as the discoveries that await us.