Updated: Jun 24
Throughout the world, more wastes are generated as the growing urban population continues to increasingly consume natural resources. As cities continue to transform to being smart, they need to incorporate environmental sustainability as one of the key agendas. They need to rethink strategies that will help in waste management and disposal systems for environmental protection against pollution.
Advanced use of technology and big data will definitely play a big role in improving urban solid waste management across all smart cities. The following steps can be taken to advance solid waste management systems in smart cities.
Using data and technology to increase operational efficiency
The use of the Internet of Things (IoT) and data for quantitative analysis has opened up a new generation of solutions and approaches to urban waste management.
Data is being used to generate insights that are expected to increase accuracy in prediction and enable greater personalized solutions. This in turn will lead to improved operational effectiveness, efficiency, and competitiveness amongst companies dealing with urban waste management.
Data tests previously dispersed can be integrated to provide information on how a waste hauler can optimize waste collections, improve on the rates of recycling waste and provide their customers with detailed information about their waste. This would improve the hauler’s operational management.
Most waste management companies also want to optimize capital planning and investments as well as decision-making on all their processes. With proper integration of back-office data, this can be achieved.
Data gathered can contain information on capacity, location, time of pickup, and vehicle assigned for pickup. This can be helpful when scheduling pickups so as to reduce congestion, fuel cost, and labor costs
With the application of big data analytics, connected devices, and cloud technologies, smart cities can easily improve on their solid waste management.
Using data and technology for optimal routing
Route optimization through advanced technology systems and data not only helps waste collecting companies to save on time, energy, and finances, it also makes pickup points eco-friendly and protects the environment.
With big data and advanced software, historical waste and recycling data collection can be used to optimally plan out routes to guide waste collecting trucks. This will not only increase efficiency in collection operations, but will also help in supporting energy efficiency by reducing harmful emissions and carbon footprint by having fewer trucks activities
Big data can also be used to garner better estimates on how much waste is produced were for better targeting and focusing.
Using data and technology for quick turnaround times
Big Data and data enable processing and analyzing large data repositories within a tolerable amount of time.
Waste management companies are also investing in feature-rich customer-facing technology. They are leveraging user-friendly mobile apps to facilitate prompt service, extra pickups, and bill payment through push notifications. Technology has greatly reduced the complexity and the cost of urban solid waste management systems making them all the more efficient, safer, and productive while reducing their environmental impact.
Using technology and data to sort waste
Recycling of data can be made more effective through big data. A recycling robot can be used to collect data and sort waste based on patterns, textures, and materials.
Smart devices like Bin-E have been used to recognize, sort, and compress waste using sensors, AI, and cameras. It then sends data to the cloud and alerts. the waste collection company once it is full. This has been known to solve the challenge of improper waste. The data stored in the integrated cloud can also be used to identify consumer consumption patterns.
The new collection, disposal, and screening technology can efficiently and quickly segregate recyclables.
Using data and technology to reduce waste creation
Big data and analytics can be used to reduce waste being created. Cities can use this to analyze and predict such things as expected consumer demands, weather patterns, and supply chain processes. This would be useful to producers & production companies in reaching optimum production levels greatly reducing wastage.