Putting The Smart in Smart Cities

 In Analytics, From the CEO, India, Internet of things, Machine Learning, Our Thinking, Smart Cars, Smart City

The Indian Government recently added 27 cities under the Smart Cities Mission. Smart cities are essentially cities which are innovating and using data, information, and telecommunication technologies to be more astute and efficient in utilisation of resources. This not only leads to cost savings and improved quality of life but also ensures better disaster management and helps reduce the cities their carbon footprint. The Centre has granted these cities Rs. 200 crores for improving their infrastructure under the programme. With this, the total number of Smart Cities chosen in the country has risen to 60. This is a testament to the era of unlocking the potential of data analytics to help government reforms. The sentiment is echoed globally with the spending on smart cities expected to reach US $1.2K by 2019.

With the advent of Internet of Things (IoT), improved Internet connectivity and proliferation of smartphones, the amount of data available is increasing every day. This data holds tremendous potential and can be harnessed to make dynamic decisions which adapt to the changing circumstances and make the smart cities smarter. Typically, data can be used for maximum impact in the sectors of mobility, environment, economy, and governance. According to a report by a market research company, from 2015 to 2050, the number of people living in cities is expected to go up from 3.6 billion to 6.3 billion. As such, this represents a pressing need to utilise data analytics to ensure that there is an efficient allocation of resources for this growing demand.

Smart Transportation

In 2012, implementing methods for smart transportation accounted for 16% of the global spending of smart cities. When most of the major cities cite traffic and transportation problems as one of the major hindrances to growth, there is an option to obtain and analyse traffic data points through APIs from Google Maps, traffic monitors, and crowdsourced reports and better manage the traffic. Smart cities use RFID tags on vehicles to track precise traffic movement. This data is then analysed and real-time management solutions are implemented. These solutions range from adjusting the traffic signals to better suit the vehicular movement, providing best routes to drivers, efficiently distributing crowds through the city road network, ensuring priority routes for emergency vehicles such as an ambulance, etc. According to a research by the US Federal Highway Administration about 25% of congestion is caused due to one-off traffic incidents. Using sensors, cameras, satellite feed, and IoT devices, the effects of such incidents can be mitigated.

Smart Energy and Resource Management

Globally 75% of the energy consumption can be attributed to cities as well as an almost equal amount of CO2 emission. Traditionally, there always has been a disparity between the consumption of resources within various pockets of a city. The availability is typically linked to historical consumption, ease of sourcing, and various local factors rather than actual real-time consumption. Smart cities aim to facilitate effective resource allocation. Such cities employ sensors to monitor temperature, water consumption, air quality, waste generation, electricity consumption amongst other things. Using big data analytics, these enormous data points are sliced and diced and logical conclusions are made to develop the most efficient energy management algorithms to make the city smart. By analysing the data, the areas are provided with resources based on their actual demand pattern. This ensures effective allocation and reduces wastage of resources. Most importantly, all smart cities stress on using renewable sources of energy to replace fossil fuels in a bid to reduce their carbon footprint.

Smart Technology and Infrastructure

Improving the infrastructure is touted as one of the fastest catalysts to socio-economic growth. Smart cities attempt to connect all the public and few private establishments and facilities and get them on the grid. One of the first implementations of a smart city is to make high-speed Wi-Fi available throughout the city. It is critical to ensure that the bandwidth should be prioritised based on need, for example, to ensure commercial and financial areas and schools receive priority during the working hours of the day. The Indian Government has decided to provide free WiFi to 25 specific cities which have a population of more than 10 lakh to facilitate better infrastructure. Smart cities take connectivity one step further and ensure that all the systems on the grid operate efficiently and on the same open platform. This infrastructure connectivity includes traffic signals, street lights, trash disposal systems, parking metres, etc., thus improving the overall productivity of the city. Many cities have even implemented a city dashboard to give real-time reports on all aspects of the city.

It goes without saying that it is critical to efficiently analyse the data given its size and complexity. Done correctly, the advanced analytics can go a long way to improving the standard of living, environment, and public safety. Clearly, big data, predictive analytics, and implementing efficient dynamic solutions based on the data analysis is the key to future sustainable cities.

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