Nokia launches smart city pilot project on Lahore’s MM Alam Road

smart city

Nokia begins pilot smart city project on MM Alam Road of Lahore and would install sensors for management of street lights, waste collection, traffic, environment and parking spaces.

In order to improve urban life, the Punjab government has launched a pilot project of ‘Smart City Lahore’. The main objectives of the project include, first the efficiency of services, optimizing the use of public resources, and providing a high level of citizen service.

Secondly, sustainability, to grow and develop the city with strong consideration to environmental effects. Thirdly mobility, to make it easy for citizens, workers and visitors, by foot, by bike, by car, by public transport. Fourthly, safety and security, to improve public safety and security.

Fifthly, healthcare, to improve the quality of health services by bridging the gap between citizens and healthcare services through fully integrated healthcare systems, sixthly utilities, by digitizing the energy sector, making the best use of water in agriculture and residential areas.

Read more: Lahore to combat environmental hazards with IoT based smart trees

The Chief Operating Officer of Punjab Safe City Authority, Kamran Khan while talking to the media said that the government had already given approval to Metropolitan Corporation Lahore to launch a pilot project on MM Alam Road and Liberty Market Parking.  

He informed that a Memorandum of Understanding (MoU) has been signed with Nokia at Expo 2020 in Dubai as Nokia had completed a smart city project in Cyprus. Nokia had started a free-of-cost pilot project on MM Alam Road and would install sensors for management of street lights, wastes collection, traffic, environment, and parking spaces.  

Chief Operating Officer of Punjab Safe City Authority said that system of traffic would be highly beneficial which will resolve the issue of traffic jams at peak hours, especially on particular points of the city. He said waste collection management would provide real-time monitoring, fill level alerts, and predictive analytics to enable decision-making well in time.  

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