Why we must use big data analytics to help save the environment

In recent years, the narrative around business intelligence and analytics has seen a sea change. Future-driven companies now understand the business value and impact of data-driven insights.

As per a recent Gartner report, business leaders must explore a combination of big data analytics and advanced AI to provide a richer context for accurate business decision-making. This will also help with the predictive analytics aspects that are increasingly becoming the front and centre of any sustainable business initiative.

Big data analytics has gained traction in recent years due to a plethora of reasons. It has helped to automate significant business decisions, analyse everything that influences businesses, and power innovation that helps save millions of dollars.

Big data analytics for the environment

Applications of big data analytics in the environmental space have many benefits.

It has helped optimise efficiency in the energy sector and will play an increasingly important role in creating smart cities and helping businesses grow sustainably. In the renewable energy sector, big data analytics and AI-powered algorithms can help construct predictive models of wind, hydroelectric, and solar power.

On a global scale, big data analytics holds the potential to solve issues related to climate change and global warming.

Several studies in the US and Europe have pointed to AI modelling and analytics that have made it easier to identify the causative agents of global warming. In follow up to this, the management of natural resources can be better handled through AI and predictive modelling of big data.

Energy and utility sectors

Indian companies in the energy and utilities sectors have greatly benefited in connecting their data from smart meters and automating their systems for energy consumption measurement, analytics and optimisation.

It can predict energy failures or redundancies, allowing businesses to gather actionable insights and make better-informed decisions concerning resource optimisation. This also has cost-savings benefits, which translates to up to a 12 percent reduction in annual electricity bills.

India’s pollution crisis

In the last two decades, air pollution has become the country’s second-largest risk factor, adding to the national disease burden. As of 2018 projections, annual deaths in India due to air pollution will rise up to 1.7 million by 2030.

Adding to this, the economic cost of air pollution is estimated to be more than $95 billion. It has affected citizens’ health, mortality, and morbidity rates, and is one of the leading contributors to climate change today.

Rapid urbanisation has resulted in India’s second major environmental threat — our rivers are choked and polluted. The main drivers of water pollution in India include inadequate infrastructure for the collection and treatment of sewage and industrial wastewater, and improper practices in the agricultural sector.

For example, cities and towns located on the banks of Ganga generate around 33 percent of wastewater in the country.

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Efficient governance

The National Clean Air Programme (NCAP) launched by the central government is a favourable initiative that is aimed to achieve 20-30 percent reduction in particulate matter concentrations by 2024. Similarly, the Namami Gange Programme, approved as a flagship programme by the union government, has been launched to effectively abate pollution, and improve the conservation and rejuvenation of the Ganga river.

Companies that offer big data analytics, AI, and IoT solutions have a huge opportunity to help bolster these initiatives. By working in tandem with central, regional, and local governments/authorities to track and monitor industry compliance with pollution control measures, they can facilitate deep analysis of environmental data for new sustainable initiatives. By working with industries to aid environmental data acquisition, monitoring and analysis, they enable them to take necessary action immediately.

Some of the benefits of employing these niche technologies in the environment sector include remote visibility and improved data availability, which makes it easier to identify high-risk areas. With proactive, real-time alerts and controls in place, they can ensure that potential hazards are kept in check.

Making the case

There is an imminent need for real-time environmental monitoring and analysis. With big data analytics, vital information on pollution levels and regulatory violations can be drawn on a national level. Industrial processes can be monitored and regulated at a granular level to ensure that environmental regulations are being followed.

Analytical tools powered by predictive and Machine Learning technologies can be used to predict location-specific air pollution severity days in advance, by feeding them with existing data on the subject.

Here are some of the benefits that are reaped when big data analytics is employed in the environment sector-

Understanding energy conservation

Measure, optimise and forecast the amount of carbon emissions in the environment, which plays a significant role in climate change. With billions of harmful emissions in the atmosphere, many industries are showing a renewed focus on cutting back their energy consumption.

Demand forecasting

Any industry must predict future values based on historical and current data. Big data analytics, AI and IoT-driven models can go a long way in monitoring everyday data, using intelligent algorithms and strategies to predict running hours and the availability of utilities for future use.

Cost savings and ROI

Apart from making the world a greener space, the other obvious application is cost savings and ROI. With systems and solutions powered by big data analytics, businesses are better placed to take quick action and correct any abnormalities. Annually, these decisions help cut costs by 35-40 percent on average.

Intelligent insights are made possible at the intersection of big data, AI-driven analytics and IoT technologies. When combined and leveraged effectively, these technologies can help combat environmental crises, while transforming the way traditional businesses run. For the Indian market, strategy is key in the coming years.

Any sustainable digital model depends on a well-framed roadmap and strategy that can contribute effectively to people, processes, and business ideologies. The capability to pinpoint sources of pollution, major pollutants and industry regulation violations in real-time, combined with efficient governance is the way forward for a greener tomorrow.