4 Applications of Big Data in Waste Management

  • Muskan
  • May 29, 2021
  • Big Data
4 Applications of Big Data in Waste Management title banner

As the population is growing, cities are expanding and so are the needs of the people culminating in waste generation. Keeping a view of that in mind, waste management needs more attention than it's given. Broadly waste management is necessary to maintain the environmental balance and adhere to the sustainable lifestyle. 

 


What is Waste Management?
 

Waste management refers to the entire process which happens from the collection of various kinds of wastes to their disposal in the correct manner. Every industry, every household generates waste which can be huge if seen at a global level. There are various kinds of wastes and depending upon its kind the techniques and manner of safe disposal is carried out. 


Obviously, the health hazards are the concern at every stage of the waste management. This process cannot be avoided, unsafely disposed of garbage and unkempt waste can cause a lot of disasters to the environment and in turn to Mankind.

 

The correct procedure of waste management reduction and reuse, animal feeding, recycling, composting, fermentation, landfills, incineration, and land application, meanwhile, can help in saving the resources, reducing pollution, saving energy, taking care of the environment and so on. 


For example: During the pandemic times a lot of surgical masks, PPE Kits, used syringes and other medical wastes have taken a surge in terms of their production. In some of the cases such components are being mishandled in terms of disposal. 

 

They are being abandoned in the open, birds and animals rummage through them, the uncut elastics of the masks strangle the beaks of the birds, cows and buffaloes end up consuming plastics which are hazardous  and the foul smell of the garbage and unforeseen diseases remain a concern.

Now just by safe waste management and disposal techniques we can ensure this does not happen. If we use the 4R of the environment carefully which is REDUCE, REUSE, RECYCLE and RECOVER, a lot of waste generation can be stopped without any burden on the municipal cooperation or the government at a personal level. 

 

Insofar as the capacities of waste management systems and hazards related to them can be eliminated  by employing certain technology at work, advanced analytics like Big Data can solve a lot of management related issues and can help in understanding the further requirements of the system to be able to dispose of the waste successfully with minimum hazards by just providing the abandoned information which is already present but hasn’t been used up to its potential. 

 


What is Big Data?
 

As data refers to the stored information and recorded operations which were performed by the computer in various forms, big data can be understood as the same data being present in huge amounts and numbers. This consists of information provided and both humans and the devices. 

 

Big data is the collection of the data which is also growing exponentially with time. Big data is so large and complex in its size and storage that it is unable to be deciphered and understood efficiently by the traditional data management tools. 

 

Big data can be used to reveal pre existing ignored patterns by using analytical understanding and predetermined conclusions are sought after  to be able to fetch the desired results and understand and decode the data in terms of existing issues. 

 

Recommended Blog: Applications of Big Data in Daily Lives 

 


Collection for Big Data for Waste Management

 

As waste management is more than just collecting huge piles of garbage and cleaning up the streets. It's a more complex task and the implementation of Big Data analytics can help in understanding the needs and adapting the practices most suited for them. 


Big data compiled, driven and utilised by the cleanliness related surveys can help in understanding the appropriate locations for the bins on the streets where they can be used efficiently. Also, this can be used to understand the frequency of bin emptying based upon the location. 


NYC and San Francisco have installed such solar powered garbage bins with sensors and compactors, once a certain filling level is reached, they alert collectors for emptying the bins. 


Big data can help in understanding the optimal garbage collecting routes, hassle free hours to do so and moreover it can help understand the area from which a particular kind of waste comes to send them to the proper recycling centres and reusing centres for easy processes. 

 

In the case of an industrial area big data tools can help in formulating proper management systems for them and understand the failures over the years. 


Big data practices can help in keeping a track record of success and failures of the management practices for the garbage and then humans can continue to modify and optimise them.

 

Recommended Blog: Big Data in Media and Entertainment 

 

 

Applications of Big Data in Waste Management

 

We've discussed some of the effective applications of Big Data in Waste Management below.  
 



Image Showing Role of Big Data in Waste Management  Artificial Intelligence Equipped Systems Vehicle Recycling Inventory Management Satellite Based Monitoring

Applications of Big Data in Waste Management


1. Artificial Intelligence Equipped Systems


Big data understanding  can pave the way for the usage and need for more advanced technology which can be used in waste management. Recycling is an important aspect in the process of waste management. Big data can provide for the data related to the kind and quantity of the waste available with the exact locations. 

 

This can help in deploying artificial intelligence based systems to do the recycling segregation, as recycling is a labour intensive process with a risk of high injury and diseases for humans. 

 

These AI based robots functioned to pick and segregate a particular kind of trash can come to be the boosters of recycling industries making it cheaper, safer and a faster process. 
 


Clarke is one such machine, this is basically a recycling robot equipped with artificial intelligence to identify and pick lots and lots of food and beverage containers to be able to separate them from the rest of the waste. 

 

More such robots can be the future of recycling. Clarke is equipped with the intelligence to identify the logos and the images on the empty packets and if it comes with a new logo it immediately stores it in the memory to be able to use it in the next round of recycling segregation. 

 

The more AI systems will be deployed in segregating, such systems will be changing the quantity of wastes that would hence go in the landfills. Machines equipped with proper data will be able to seek and categorize the most different kinds of recyclable products. Waste management at superhuman speed. 

 

Recommended Blog: Applications of AI in Retail Sector 

 


2. Vehicle Recycling


The more people are being asked to use public transport the more they are inclined to buy their own cars, ironically. Considering the average lifespan of a car and the limit of the older cars on the roads, some get out of the operation for other reasons like disaster and other such conditions. 

 

This one question takes up the mind of what is feasible to do with the old and unused obsolete vehicles. 


Big data can help in understanding the quantity and location of car abandonment. This can help the scrap and salvaging centres to take the needed and reusable parts of that vehicle before it gets totalled. This enables such businesses to get the maximum payout and also reduces the heap of probable dump. 

 


3. Improved Inventories 


Big data can help in the improvement of inventories by clarifying how much of a product is needed in every industry so that neither the excess of something is produced nor purchased to eventually get wasted. 

 

In the times of crisis the excess is stocked and piled up by certain industries which never gets used, big data analytics however can help in pre determining the required quantity to some extent. 


For example: In the pharmaceuticals, the medicinal stock gets outdated and the treatment cannot be the same for everyone. In such cases the stocked medicines and products of different kinds get wasted. 


Just like the excess purchase of a middleman gets wasted if bought too much.
In such cases information can be collected by big data to avoid waste is really helpful for the initial aspects of waste management which is waste generation. 

 

This information can be cross-referenced to other information like, the demand of the product in the market, users in the immediate demographic location, the medical history of the patients, efficacy of the medicine and so on to validate the information provided by the big data tools. 

 


4. Satellite-Based Monitoring 


Satellite data can be a huge tool to get a clear insight into what is being done to the natural resources which is somehow deterring the capacity of the environment. The Amazon forest is diminishing, the great barrier reef is dying, pacific garbage patch is increasing. 


Big data can help in environmental degradation by human activities is by using satellite data and cameras to keep an eye on the damage being done by human activities and based on that data the clear measures to safeguard can be found. 


The warming of water due to global warming is bleaching the coral reef, huge ships are dumping sewage and garbage in the seas, landfills are being made out of potentially fertile land , there are such problems which can be solved for the goodness of the environment only if we possess the correct ability and tools to be equipped with that.

 

Recommended Blog: Companies that use Big Data 

 


Conclusion


The waste management issue is real but as the technological aspects are taking a lead it is possible to understand the problems and tackle them. 

 

Big data information combined with roles like artificial intelligence, satellites, citizen involvement and participation is keeping the waste management systems well prepared to deal with the crisis by finding serious conclusions while rummaging through huge data available from various locations and aspects. 

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