Big Data for planning

By Author  |  Published: 10th Nov 2017  12:55 amUpdated: 11th Nov 2017  2:46 pm
Big Data
Efficiencies in traffic management, water storage, air-cooling and heating systems will improve.

According to infrastructuretoday, Digital India will be considered as a fulcrum for development of Smart Cities. Through its tripartite objective of creating digital infrastructure, timely delivery of digital services on demand, and digital empowerment of citizens, the Digital India programme builds the digital backbone of Smart Cities across the country.

What is the role of technology in Smart Cities Mission?

As per a paper published by International Journal of Science and Research (IJSR), currently, 31 per cent of India’s population lives in cities. These cities also generate 63 per cent of the nation’s economic activity. These numbers are rapidly increasing, with almost half of India’s population projected to live in its cities by 2030. To accommodate the needs of this growing citizenry, India must rebuild or refurbish its existing cities, especially the ones that are selected to be a part of Smart Cities Mission. While doing so, it must weave in the latest and greatest advancements in technology into its blueprints for cities. That includes those in Artificial Intelligence, Machine-to-machine communication and Big Data Analytics.

How does Big Data help?

Big Data is the term given to large volumes of structured and unstructured data that can no longer be processed by traditional databases. The Digital India programme will see to it that the cities of the future will have digital infrastructure that can store yottabytes of data. Most of it would be unstructured and that is where Big Data analytics comes in. It uses advanced techniques like predictive modeling, text analytics, machine learning, forecasting and statistical analysis to reveal hidden patterns, unknown correlations and other important information that aid decision-making.

Let’s look at some of the use cases of Big Data Analytics in Smart Cities according to IJSR:

Smart Grid Efficiencies : A Smart Grid is an electricity network based on digital technology that is use to supply electricity to consumers. Each device on the grid can have sensors to gather data – power meters, voltage sensors, fault detectors, to name a few. It uses Big Data for monitoring, and analysis within the supply chain to help reduce energy consumption and maximize the transparency of the energy supply chain. Let’s look at a few efficiencies created by Big Data :

Outage management: The smart grid directly reports outages and documents its recovery in real-time.

Forecasting based on seasonality: Patterns of consumption of energy can be gleaned from the data to understand where and when the consumption will be high and when it would be low.

Asset management: Big Data Analytics can predict how distribution grid assets are about to fail and helps in determining how costly or dangerous those breakdowns are going to be.

Mobile workforce management: Systems on the smart grid can be monitored in real-time to identify the location of the fault and thus mobilise workforce accordingly.

Behavioural analytics of the consumers: The consumption patterns of the consumers can be analyzed according to time, place and utility plan. Thus Big data provides data on consumer behaviour touted to be the holy grail of profitable businesses.

Traffic congestion management : By 2050, the urban areas in India are expected to grow by 404 million people.. Rapid urbanisation is concern in India as it is causing traffic congestion. One of the key elements of the plan of Smart Cities is the ability to implement Intelligent Transport Systems (ITS) to deliver city wide mobility services. A proper congestion management plan factors in ever-exploding vehicle population on the road, geometry of the city roads and travel needs of citizens. For this, data is collected from sensors on signals, GPS trackers, social media posts, mobile phones and cameras. Let’s look at a few efficiencies created by Big Data :

Reduces accidents: Traffic department can predict where congestion is likely to be high and warn the commuters who take a detour and avoid congestion-related accidents.

Future trends: Combining historical data with real-time data, the congestion patterns across time and place can be arrived at using predictive analytics.

Pattern of traffic and behaviour: Big Data Analytics can help in analysis of the historical data to gain understanding of patterns of behaviour of traffic and road incidents.

What’s the big picture ?

Both, Big data usage and smart cities are still novel in application if not in concept. With the cities leaving such a huge digital footprint, especially with data coming in from Internet of Things networks, Big Data is likely to emerge as the most important technology that collects, analyzes and predicts consumer behaviour over and above creating efficiencies in areas like smart traffic management, smart water storage, air-cooling and heating systems and smart waste management. The case for Big Data has never been bigger.