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IoT And Predictive Analysis’ Impact On Indian Transport Industry

The future of transportation in India, if it continues along the technologically-enlightened path that it has embarked upon, could be smoother and less chaotic in the near future.

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The 33 Red Buses of Glacier National Park, nicknamed “The Rubies of the Rockies,” on average, transport 60,000 tourist each summer.
The 33 Red Buses of Glacier National Park, nicknamed “The Rubies of the Rockies,” on average, transport 60,000 tourist each summer.

A report in the Wall Street Journal predicts that India’s combined workforce will increase by 12 million each month, making it the youngest working population in the world by 2022.

Sixty-five per cent of India’s population already falls in the working-age bracket, which means that a considerably large group of commuters from across the country travel long distances using personal vehicles and public transport. In doing so, they often battle with ill-maintained roads and insurmountably heavy traffic. A more specific viewpoint, focusing on commuters using company-sponsored cab services, reveals that these professionals spend hours traveling to and from work, with ill-planned routes and delayed pick-ups hampering their health and workplace productivity.

Therefore, several path-breaking companies are leveraging the potential of modern-day technologies to bridge the existing gaps in India’s transport sector.

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Indian Railways is one of the most important and controversial transport in India. Wikimedia Commons

This is where the role of Internet of Things (IoT) and predictive analytics in ride-sharing comes in. The objective of every ride-sharing start-up is to find a solution to optimize travel. They use IoT and Artificial Intelligence (AI) to identify demand and supply patterns for transportation within the city, based on historical data. The final objective of commute-focused start-ups is to understand how the traffic from commercial hubs interacts with the rest of the city and identify a way to alleviate the hassle of ride-sharing within that context.

The Indian transportation industry can leverage predictive analysis and data mining to draw insights and patterns from the vast pool of big data pertaining to transport and traffic conditions in particular areas. Using these patterns, systems powered by AI can plot the fastest routes for commuters, factoring in multiple pick-ups and drops on the way. Such systems rely upon AI to create routes for corporate commutes and club the employees who plan to commute at similar times, thus ensuring that they take the shortest route possible.

Predictive analysis tools can also alert drivers and passengers about impending bottlenecks and congestion. Such systems will reduce travel time for employees, while helping corporates save the large sums of money they spend on organising company-sponsored commutes.

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The objective of every ride-sharing start-up is to find a solution to optimize travel. They use IoT and Artificial Intelligence (AI) to identify demand and supply patterns for transportation within the city.

Technological intervention can also bring about safety and security as far as public transport and employee commute services are concerned.

Corporates with 24-hour rotational shifts are obliged to provide cab services to their employees to ensure their safety. Connected services such as transport automation systems, driven by AI and IoT, can ensure that employees travel safely by collecting and storing relevant data about drivers, including their background verification information and prior criminal records. Additionally, through robust mobile applications, passengers can provide feedback pertaining to their experience with their drivers at the end of each trip. Advanced systems that use mobile phone sensors can also identify instances of rash driving.

Beyond the workforce commute, predictive analysis can be applied to a holistic urban mobility scenario. It can improve public transport by forecasting weather conditions, determining arrival times of buses, and predicting the number of drivers travelling each day.

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Hand pulled ricksaw and tram in Kolkata. wikimedia

Further, advanced analytics will be able to provide data regarding the impact of road maintenance, signal failures, accidents, and vehicle breakdowns on the overall traffic conditions, in addition to circumnavigating mobility bottlenecks by mapping the shortest routes in real-time. This will help people in reaching their destinations as quickly as possible.

Also Read: Indian Catholic Nuns Call Out For Justice in Kerala

The future of transportation in India, if it continues along the technologically-enlightened path that it has embarked upon, could be smoother and less chaotic in the near future. On the back of rapid technological advancement, the transport sector has the potential to transform itself into a well-oiled machine. Commuters and travelers are advised to just sit back, fasten their seat belts, and enjoy the ride. (IANS)

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Apple’s Recycling Robot Is Capable of Disassembling 200 iPhones Per Hour

In 2018, the company refurbished more than 7.8 million Apple devices and helped divert more than 48,000 metric tons of electronic waste from landfills. 

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Apple has received nearly one million devices through its programmes and each Daisy can disassemble 1.2 million devices per year. Pixabay

 Apple on Thursday announced to expand its global recycling programmes and introduced Daisy, its recycling robot that is capable of disassembling 200 iPhones per hour.

US customers can send their iPhones to be disassembled by Daisy which is 33 feet long, has five arms and can methodically deconstruct any of 15 iPhone models.

Daisy will disassemble and recycle select used iPhones returned to Best Buy stores throughout the US and KPN retailers in the Netherlands, the company said in a statement ahead of Earth Day that falls on April 22.

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For cobalt, which is a key battery material, Apple sends iPhone batteries recovered by Daisy upstream in its supply chain. Pixabay

Apple also announced the opening of its “Material Recovery Lab” dedicated to discovering future recycling processes in Austin, Texas.

The Lab will work with Apple engineering teams as well as academia to address and propose solutions to today’s industry recycling challenges.

“Advanced recycling must become an important part of the electronics supply chain, and Apple is pioneering a new path to help push our industry forward,” said Lisa Jackson, Apple’s vice president of Environment, Policy and Social Initiatives.

Apple has received nearly one million devices through its programmes and each Daisy can disassemble 1.2 million devices per year.

In 2018, the company refurbished more than 7.8 million Apple devices and helped divert more than 48,000 metric tons of electronic waste from landfills.

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The Lab will work with Apple engineering teams as well as academia to address and propose solutions to today’s industry recycling challenges. Pixabay

Daisy can take apart iPhones to recover materials such as cobalt, aluminum and tin, which are then recycled back into the manufacturing process.

Once materials have been recovered by Daisy, they are recycled back into the manufacturing process.

Also Read: Parkinson Treatment Possible Through A Blood Pressure Drug

For cobalt, which is a key battery material, Apple sends iPhone batteries recovered by Daisy upstream in its supply chain.

They are then combined with scrap from select manufacturing sites and, for the first time, cobalt recovered through this process is now being used to make brand-new Apple batteries. (IANS)