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  • 2024/07/06 02:03
• This is about to change as the bigger transformation is underway

  The evolution of technology over the years is pushing boundaries color knotter device and changing the way world conducts its business. The advent of internet and everything being accessible easily has made life comfortable and easy. Transport and logistics industry is one of the leading segments investing heavily in IoT. IoT is enabling smart transportation which has rapidly changed the industry with the help of cutting- edge technologies along with mobile connectivity, creating a seamless interface. To make transportation and logistics industry a more effective and efficient system, IoT has made it all possible from effective road safety issues to monitoring of the system in fleet management.

  Businesses seek real-time fleet information so that they can reap long term benefits by making intelligent real-time decisions and IoT has enabled the same at low costs. In a simplified way the use of IoT enables one to keep track of operational efficiency including better turnaround time, fuel consumption, managing the wear and tear of tyres, accident response, monitoring, and route navigation, which results in optimizing long term business solutions. It also enables smart inventory management which is most crucial for a business and gives real-time information about warehousing, distribution and production centres. It has increased productivity in the supply chain, minimizing costs and errors.Although IoT has made impressive headways in the transport and logistics sector, the focus has been on using it as correction based technology rather than making it preventive technology, to fill in the vacuum that has long been a part of this industry.

  This is about to change as the bigger transformation is underway with the combination of IoT and Machine Learning (ML), being a game-changer for this industry. The availability of huge amount of data through IoT and cheaper computing are giving a fillip to companies looking to harness the power of Machine Learning. ML techniques can predict a defined problem using supervised learning or even find hitherto unidentified patterns utilizing unsupervised learning algorithms.The use of IoT in transport industry has increased accountability, efficiency and transparency in the system while making it cost-effective in its current form. But the industry will witness far more substantial benefits in near future with the advent of mass solutions combining IoT, Machine Learning and Artificial Intelligence which will define the future of this industry in scaling up.

  To remain competitive and enhance efficiency, keeping up with the latest technology is a must. The logistics industry is benefiting immensely from the latest technology and will continue to grow as more advances are made. The breakthroughs in technology will continue to push the boundaries for years to come.-Rohit Chaturvedi, CEO- Transport HubDisclaimer: The views and opinions expressed in this article are solely those of the original author. These views and opinions do not necessarily represent those of Deccan Chronicle and/or other staff and contributors to this site.

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  • 2020/08/31 12:28
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• The-Kepler-90-system-also-sweater-machine-Manufacturers
  The Kepler-90 system also sweater machine Manufacturers could have a ninth planet or more, according to the researchers. It is 2,545 light-years away; a light-year is 5.8 trillion miles.Google used data collected by NASAs keen planet hunter, the Kepler Space Telescope, to develop the machine-learning computer program. It focuses on weak planetary signals - so feeble and numerous it would take humans ages to examine.While machine learning has been used before in the search for exoplanets - planets beyond our solar system - its believed to be the first time an artificial neural network like this has been used to find a new world."This is a really exciting discovery, and we consider it to be a successful proof of concept to be using neural networks to identify planets, even in challenging situations where the signals are very weak," said Christopher Shallue, a senior software engineer at Google in Mountain View, California.NASA astrophysicist Jessie Dotson, the Kepler project scientist, is "so excited to see where this goes next."
  "Who knows what potential insights might be gained," she said.Shallue teamed up with astronomer Andrew Vanderburg of the University of Texas at Austin to develop the program. They essentially trained a computer to identify exoplanets based on Keplers observations in changing stellar brightness - the subtle, fleeting dip in a stars brightness when a planet passes in front of it.The two used a technique similar to what had been previously used by others to enable machines to distinguish between pictures of cats and dogs.Besides identifying Kepler-90i, the machine-learning program also confirmed an exoplanet missed by astronomers in yet another solar system: Kepler-80g, the sixth planet in that particular solar system.Shallue and Vanderburg plan to keep up the hunt, using the program to scour the 150,000-plus stars observed by Kepler.In all, more than 3,560 exoplanets have been confirmed to date - two-thirds of them spotted by the 2009-launched Kepler - with another approximately 4,500 candidates awaiting verification.
  It will be up to more advanced telescopes, like the James Webb Space Telescope targeted for launch in 2019, to study the atmospheres of these distant worlds and sniff out any traces of possible life, Vanderburg noted.Shallue said Google plans to release all the code needed for someone to join the exoplanet search, using a basic home computer and the publicly available Kepler data. No specialized hardware should be needed, he said.Neither NASA nor Google expect to put astronomers out of business. Shallue sees this as a tool to help astronomers have more impact and increase their productivity."It certainly will not replace them at all," he assured reporters.Machine learning computer systems, which get better with experience, can outperform people in a number of tasks, though they are unlikely to replace people in all jobs, a study has found.
  • sweater-machine
  • 2020/07/27 10:29
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