Solution can deliver an additional 15-25 per cent in savings – on top of the 50 per cent energy savings from LED lighting alone
Tata Consultancy Services (TCS) has launched “intelligent software” that aims to rapidly reduce the payback period on investment in LED streetlights.
According to TCS, its Intelligent Urban Exchange (IUX) platform will allow cities to invest in other smart city projects sooner, cuts energy consumption using self-learning algorithms and improves public safety by responding to real-time changes in traffic, weather and people movement.
The global IT services, consulting and business solutions firm claims the typical four- to five-year payback period will almost be halved to between two and three years.
“The global switch to smart street lighting is an open invitation for every city to begin their smart city journey,” said Seeta Hariharan, general manager and group head, TCS Digital Software & Solutions Group.
“Like the dawn of the internet, we’re just scratching the surface of what’s possible when cities intelligently connect scores of new urban data sources. Just as we’re seeing in retail, banking and other customer-centric markets, cities will compete on their ability to deliver a superior experience for digitally savvy citizens and visitors.”
Available from TCS Digital Software & Solutions Group, IUX for “adaptive streetlight optimisation” also helps cities to jump start smart city projects in other domains, such as water and transportation, by leveraging smart streetlight wide area networks and a common data analytics platform, the company said.
The cloud-based IUX software capitalises on ambitious efforts by cities of all sizes to replace power-hungry conventional streetlights that consume 40-50 per cent of a typical city’s energy budget. Designed for both LED and conventional streetlights, it acts like a virtual energy advisor for mayors, city managers and urban planners.
IUX can deliver an additional 15-25 per cent in savings – on top of the 50 per cent energy savings from LED lighting alone – by optimising streetlight operation using machine learning and predictive analytics on real-time and historic data, TCS claims. It enables individual streetlights to respond to real-time events by automatically adjusting city lighting to suit changes in crime patterns, traffic, people movement, and weather.
For example, streetlight luminosity can be automatically increased to enhance public safety when crowds amass around a traffic accident waiting for first responders. The software can also recommend streetlights be dimmed to save money when bad weather keeps people indoors, increased in response to pedestrian activity or adjusted to resolve light pollution complaints.
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