Best Data Science Applications in Waste Management

  • Using Satellite Information to Protect Our Oceans

The Australian government is doing everything possible to save the Great Barrier Reef, which is on the verge of extinction. Warming seas are hastening coral bleaching and causing long-term harm to this natural resource, according to experts. Using satellite sensors and data processors to identify environmental hazards in the waters is one way big data can help prevent further environmental harm. Scientists can determine the environmental impacts of shipping routes by looking for patterns in ship paths. This information could be used as the basis for regulatory investigations and enforcement actions.


Vehicle recycling

Even though the average car lasts ten years and 200,000 miles, many vehicles last far longer. The mismatch is perhaps made worse because 17.6 million new cars are bought annually in America. Where are all the old ones going if we buy so many new cars? The response serves as another example of how big data is reshaping the waste industry. Numerous autos become useless due to natural disasters like storms and floods. Large numbers of automobiles are affected by the harsh weather, which results in excess inventory for scrap yards and garbage haulers. Many of these cars are totaled, but some of them are broken down for parts after the recalled parts are taken out. 


Scrap and salvage centers and auction sites can improve the processes they use to handle impacted vehicles by using big data to identify disaster-related car abandonment trends and comparing that information with recall databases. As a result, more vehicles can be used instead of ending up in the scrap yard, and salvage companies are able to increase owner payouts, improve part distribution, and maintain the flow of totaled vehicles. Check out the trending Data Science Certification Course in Delhi to gain profound knowledge about using data in recycling. 


  • Analytical GIS

Recently, the Swedish city of Stockholm looked into the possibility of utilizing big data to address its issues with municipal garbage. The primary objective of their inquiry was to utilize GIS to identify inefficiencies in the city’s waste collection route and to offer recommendations for future modifications based on their studies. The city created a sizable dataset with roughly 500,000 data points, including waste fractions, weights, and collection sites. They created several new waste management maps and then batched and geocoded the selected entries.


Following a preliminary investigation, comprehensive maps of a few selected routes were developed, and their efficacy was assessed using a unique efficiency indicator.


  • Robots for Recycling With AI

Recycling has always required a lot of labor and has an unexpectedly high rate of worker injuries. Because of clever machines that have replaced mainly the human component, solid waste recycling is now cheaper, safer, and far more effective. Clarke is one such device resulting from a collaboration between the Carton Council and two Denver-based companies. A recycling robot named Clarke uses artificial intelligence to recognize a variety of food and drink containers so that it can actively separate them from the rest of the recycling waste. 


A commercial robot used for 20 years in other industries is used in the Clarke project. Clarke has constantly advanced its recycling data capabilities, with near-perfect accuracy and a current pace of 60 cartons of recyclables each minute. The packaging contains symbols that Clarke is programmed to recognize, including logos; after seeing them for the first time, it picks up on the new patterns and uses them in the subsequent round of sorting and grabbing. The waste management system can sort at superhuman speeds as the AI quotient rises based on accumulated solid waste data, diverting material for reprocessing that would otherwise end up in a landfill.


Hope this article was informative enough. For more information, visit the IBM-accredited Data Science Course in Delhi and master the current data science and AI tools to assist in industries. 


1 thought on “Best Data Science Applications in Waste Management”

  1. يُنصَح عند تنظيف المنزل من الغبار والأتربة البدء بتنظيفه من الأعلى إلى الأسفل، وذلك لأنّ الغبار سيسقط من الأسطح العلويّة أثناء تنظيفها، وسيستقرّ على الأسطح الموجودة أسفل منها، ويمكن اتّباع الاستراتيجيّة التالية أثناء التنظيف: تنظيف المراوح المعلقة بالسقف ومصابيح الإضاءة، ويفضّل استخدام قطعة قماشٍ نظيفةٍ أو رطبةٍ، أو منفضة الألياف لذلك. تنظيف الجدران والأبواب، ويمكن استخدام قطعة قماشٍ نظيفةٍ، وزجاجة رذاذ مليئة بالماء للتنظيف، مع الحرص على تنظيف الزوايا والشقوق الموجودة على الأبواب أو الجدران أثناء ذلك. تنظيف النوافذ باستخدام قطعة قماشٍ نظيفةٍ ومنظف النوافذ وفي حال ظهور أيّ خطوط على الزجاج فيمكن استخدام ممسحة نظيفة للتخلص منها، واستخدام قطعة نظيفة أخرى ورذاذ الماء، لتنظيف عتبة النوافذ من الغبار. تنظيف الأسطح والبدء بإزالة جميع الزخارف الموجودة على الأسطح، كالطاولات، وخزانة الكتب، ثمّ إزالة الغبار عنها باستخدام منفضة الألياف، وفي حال بقاء آثار من الغبار، فيمكن استخدام قطعة قماش مبلّلة بالماء لمسحها. تنظيف الزخارف بقطعة قماشٍ مبللةٍ بالماء قبل إعادتها إلى مكانها، ولا ينصح بنفضها من الغبار وهي مكانها، لأنّ ذلك سيتسبب في انتقال الغبار إلى الأسطح المجاورة لها. غسل البياضات كالستائر، والملاءات، وأغطية الوسائد مع الالوان المماثلة لها في الغسالة، ثمّ تجفيفها، أو نشرها على منشر الغسيل.

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