Data Analytics in Waste Management
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.
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.
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. Some of the
major 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.
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 pay-out 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.
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.
Reference:
·
https://www.analyticssteps.com/blogs/4-applications-big-data-waste-management
ISME Student Doing internship with Hunnarvi
Technologies Pvt Ltd under guidance of Nanobi data and analytics. Views are
personal.
#DataAnalytics #WasteManagement
#WasteAnalytics #DataDriven #SustainableAnalytics #WasteReduction #SmartWasteManagement
#WasteOptimization #AnalyticsForGood #WasteAnalyticsInsights #DataScience #CircularEconomy
#WasteAnalyticsSolutions #WasteIntelligence #BigDataWasteManagement #
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#hunnarvi
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