Improving waste management with big data
Over the past few decades, waste management has become an important issue in the United States. As Americans consume more, they inevitably create more waste that needs to be disposed of. According to the Environmental Protection Agency, the population of the United States created approximately 250 million tons of trash in 2010. In response to these growing demands, the American waste management sector has grown into an $85 billion a year industry, according to a report published by First Research.
Operational costs for these businesses are not cheap, however. Trucks, manpower and resources can be a major expense for waste management companies. One Finnish business, however, is attempting to reduce the costs of operating a waste management enterprise with the help of data analytics. GigaOM reported that Helsinki-based Enevo is using big data solutions to develop technology that could help waste disposal businesses make their operations more efficient. By installing sensors in individual trash receptacles, researchers can monitor variables such as volume and temperature to determine the most optimal time for workers to dispose of their contents. Waste management companies could use this information to create more efficient collection routes as well as time the duration between visits.
There are many potential benefits to this big data application. From the consumer standpoint, receptacles will be emptied before the volume of waste becomes too unmanageable, leading to fewer overflows. For waste management businesses, collection efforts can be more effective with fewer trips being made to collect bins containing little to no trash. This can lead to fewer expenses being spent on trucks, payroll and other resources. Enevo CEO Frederik Kekalainen told the news outlet that his existing customers have reduced their logistics costs by 30 percent as a result of this initiative.
Data analytics solutions can be leveraged by practically any industry in order to improve efficiency and reduce unnecessary spending. With Hadoop big data software, analytics teams can customize a product to fit their specific needs.
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