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Big Data can be used for strategic

Big Data can be used for strategic policy making in almost any field and the Greater Manchester Waste Disposal Authority (GMWDA), England’s largest Waste Disposal Authority, has turned to Big Data to better plan their services. In order to do that, they are collaborating with the University of Manchester who uses the data generated by the GMWDA. Together they help create environmentally sustainable solutions for Manchester and the 1.1 million tonnes of waste that is produced each year.

Waste is an important aspect of societies and getting rid of it links societies with all the economic and consumption practices that we are so familiar with as well as how we can improve our environment. Big Data can greatly contribute to that and help governments better understand what’s going on and how they can incentivy citizens to improve their lives.

How the GMWDA applies Big Data, as can be seen in this video, is only one way to improve urban waste management. In many cities around the world, Big Data practices are used to reduce waste and improve waste management. In the city of Songdo for example, a true smart city in the making, citizens have to use a chip card to dispose their garbage. This enables the government to measure how much waste is disposed of when and where. In addition, sensors are placed inside the containers that measure all kinds of data. When combined with usage trends data or historical data, cities can forecast when the ideal moment is to empty the containers as well as optimize waste collection routes.

Researchers in Ethiopia are even combining geographic and socioeconomic data to better understand how household waste is spatially distributed to better manage waste practices for the whole city. Researchers from the University of Stockholm are using Big Data to identify how waste collection routes in the city can be optimized. Using a wide variety of data such as roughly half a million entries of waste fractions, locations and weights they were able to develop waste generation maps of Stockholm, revealing quite a few inefficiencies.

Big Data has only recently started to be used by local governments, but urban waste management is only one application of Big Data that we will see a lot more in the smart cities of the future. There are a wide range op applications ranging from public safety, traffic management or water management that can be optimized using Big Data. The smart city of the future will be a lot more effective and efficient thanks to Big Data analytics.
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Big Data can be used for strategic policy making in almost any field and the Greater Manchester Waste Disposal Authority (GMWDA), England’s largest Waste Disposal Authority, has turned to Big Data to better plan their services. In order to do that, they are collaborating with the University of Manchester who uses the data generated by the GMWDA. Together they help create environmentally sustainable solutions for Manchester and the 1.1 million tonnes of waste that is produced each year.

Waste is an important aspect of societies and getting rid of it links societies with all the economic and consumption practices that we are so familiar with as well as how we can improve our environment. Big Data can greatly contribute to that and help governments better understand what’s going on and how they can incentivy citizens to improve their lives.

How the GMWDA applies Big Data, as can be seen in this video, is only one way to improve urban waste management. In many cities around the world, Big Data practices are used to reduce waste and improve waste management. In the city of Songdo for example, a true smart city in the making, citizens have to use a chip card to dispose their garbage. This enables the government to measure how much waste is disposed of when and where. In addition, sensors are placed inside the containers that measure all kinds of data. When combined with usage trends data or historical data, cities can forecast when the ideal moment is to empty the containers as well as optimize waste collection routes.

Researchers in Ethiopia are even combining geographic and socioeconomic data to better understand how household waste is spatially distributed to better manage waste practices for the whole city. Researchers from the University of Stockholm are using Big Data to identify how waste collection routes in the city can be optimized. Using a wide variety of data such as roughly half a million entries of waste fractions, locations and weights they were able to develop waste generation maps of Stockholm, revealing quite a few inefficiencies.

Big Data has only recently started to be used by local governments, but urban waste management is only one application of Big Data that we will see a lot more in the smart cities of the future. There are a wide range op applications ranging from public safety, traffic management or water management that can be optimized using Big Data. The smart city of the future will be a lot more effective and efficient thanks to Big Data analytics.
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Big Data can be used for strategic policy making in almost any field and the Greater Manchester Waste Disposal Authority (GMWDA), England’s largest Waste Disposal Authority, has turned to Big Data to better plan their services. In order to do that, they are collaborating with the University of Manchester who uses the data generated by the GMWDA. Together they help create environmentally sustainable solutions for Manchester and the 1.1 million tonnes of waste that is produced each year.

Waste is an important aspect of societies and getting rid of it links societies with all the economic and consumption practices that we are so familiar with as well as how we can improve our environment. Big Data can greatly contribute to that and help governments better understand what’s going on and how they can incentivy citizens to improve their lives.

How the GMWDA applies Big Data, as can be seen in this video, is only one way to improve urban waste management. In many cities around the world, Big Data practices are used to reduce waste and improve waste management. In the city of Songdo for example, a true smart city in the making, citizens have to use a chip card to dispose their garbage. This enables the government to measure how much waste is disposed of when and where. In addition, sensors are placed inside the containers that measure all kinds of data. When combined with usage trends data or historical data, cities can forecast when the ideal moment is to empty the containers as well as optimize waste collection routes.

Researchers in Ethiopia are even combining geographic and socioeconomic data to better understand how household waste is spatially distributed to better manage waste practices for the whole city. Researchers from the University of Stockholm are using Big Data to identify how waste collection routes in the city can be optimized. Using a wide variety of data such as roughly half a million entries of waste fractions, locations and weights they were able to develop waste generation maps of Stockholm, revealing quite a few inefficiencies.

Big Data has only recently started to be used by local governments, but urban waste management is only one application of Big Data that we will see a lot more in the smart cities of the future. There are a wide range op applications ranging from public safety, traffic management or water management that can be optimized using Big Data. The smart city of the future will be a lot more effective and efficient thanks to Big Data analytics.
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