Big data analytics is pretty much a buzz in IT and almost everyone is aware that it is used the most in finance, social media, and healthcare sectors. However, there are some unusually interesting areas where it’s being used. Let’s check out some of them.
Weather forecasting using satellite data from meteorology departments is a well-known fact and is an age-old technique used to predict the weather. However, most modern-day cell phones come equipped with light, pressure, and temperature monitoring sensors which can also be used to collect weather data from the ground location. This data beamed and aggregated in data centres is also used for weather reporting using real-time analytics techniques.
Real-time location-enabled data used by commuters from smartphones are already being used to predict traffic congestions, which indeed alerts the drivers to take a detour. It’s a well know fact that this service is already provided by Google maps. This not only saves time and fuel by taking a detour but also avoids vehicle pile-ups in traffic-prone areas. The really interesting part would be useful when self-driving cars become a reality and would automatically re-route to reach a destination by the best route. This idea is not too far away either.
Most Indians would undoubtedly agree that Indian food tastes better when compared to any other continental cuisines (although we might have an occasional craving for continental food). But what’s more interesting is the fact that many nations have figured out that a lot of people find Indian food very tasty. The reason for that is strange when the food pairing techniques are compared with the recipes of other nations. Food pairing is a process which is followed while devising a recipe. The study has led to an understanding that traditional Indian recipes were carefully engineered by our ancestors instead of being just stumbled upon. This might be one of the reasons why traditional Indian food is not just tasty but also regarded as highly medicinal.
The idea of arranged marriages and one partner for life is very uncommon outside India and China. In fact, the gen X and Y population, even in India and China, seem to be open to the idea of choosing a partner by dating – which works on the trial and error principle. Several dating websites which provide these services are already using analytics for profile matching. The data points collected are not just a one-time activity while registering for the services of a dating website. The data for profile matching is continuously gathered from social media websites and the online activity of individuals. This is what is called a digital horoscope!
The Silicon Valley of India, Bangalore, alone generates close to 5000 tons of waste a day. India generates 150 million tons of waste per day. The problem of handling this is not at the final stages in waste processing plants or at the dumping grounds. It, in fact, starts from waste generation & segregation right from our homes. What if our garbage bins come equipped with sensors that alert individuals to effectively manage their waste more responsibly or recycle some of the waste at their homes at micro levels. This indeed could be rewarded with some brownie points that can be reimbursed for essential services. A smart city of Songdo in South Korea has already implemented such a plan where citizens are already using smart chip-enabled devices for garbage disposal. These micro sensor-enabled devices integrated into garbage bins (smart bins) would gather the amount of waste by weight that’s disposed of on a daily, weekly and monthly basis.
At the other end of the spectrum of the waste processing plants, Big Data analytics has enabled us to figure out the highest contributors of waste at a macro level. This data indeed enables the governing bodies to devise policies, which could bring about changes in the manufacturing process in several ways. A simple example would be to include materials in the manufacturing process, which is environmental-friendly while recycling (increase the percentage of bioplastics used in most consumer electronics products).
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