Between 1991 and 2017, India has seen enormous economic growth. India’s growth, credited to strategic economic reforms since 1991 according to an IMF working paper, has...
The cities of tomorrow are built on data
3 mins read
If you live in a city, chances are, you are quite familiar with these scenarios: it takes you 40 minutes to travel five kilometres, you stand in long queues to simply get cash out of an ATM and the only way you can effectively follow social distancing is by locking yourself indoors because there is no way you can keep six feet distance from people out on the streets. In this blog, Tata Communications' Praveen Arora, Vice President - Internet of Things (Business Unit), explains why these are only some of the unique challenges of mass urbanisation; or, everyday life as you know it.

This is where predictive analytics play a crucial role - helping cities improve mobility, infrastructure and resource management in a cost-effective manner. Identify the patterns and then break them Predictive analytics can unlock hidden patterns. Imagine if we could forecast how traffic on a street is impacted due to monsoon or how rescheduling the sequence of traffic signals by few seconds can reduce the number of cars, resulting in less pollution. Multiple simple and effective solutions can be identified through analytics."With the increasing number of Internet of Things (IoT) sensors and devices deployed across urban areas, the solution could very well lie within the data gathered from these cities. If analysed regularly and accurately, data could offer insights on your city’s strengths and pain points to facilitate informed decision making that can help create an equitable lifestyle."
"During these times, we have seen few countries who have been able to track and fight the pandemic by conducting timely analysis of data generated through IoT devices in real-time. They have successfully leveraged data science to develop a monitoring system to identify and assess every citizen’s travel history and the level of exposure to the virus."

- Public safety
- Employee or worker safety
- Upgraded mobility
- Effective waste management
- Sustainability and growth
The data can aid owners of the premises and authorities to strategies the workforce, usage of electricity and the success ratio of this initiative. As"A simple insight based on usage data and seasonal patterns can suggest best mode of energy optimisation from a renewable source or a simple control of smart street lights or building lighting control based on movement can significantly reduce carbon footprints. For instance with discussions around malls, shops and eateries to be open for 24/7 in Mumbai, here predictive analytics can monitor the number of footfalls."

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