AI to resolve problems of ‘Common Man’ – Garbage Collection
Factors contributing to ‘Collection of Garbage’
Poor Participation and Negligence by ‘Common Man’
Challenges(problems) created & its impact:
Frequency and Volume, unplanned urban development, Garbage Apathy, Administrative / Operational Management
Some key ingredients to make this work –
1.?Authentic data – This will help in understanding the “contributing Factors’
a.?Demographic Diversity – Urban areas and Rural areas need localised solution for garbage collection. The ‘quality, ingredients and volume’ differs vastly.
b.?Frequency and Volume – This is directly linked with improved economic upliftment. Disposable bulk items like furniture, electronic goods become garbage much quicker and in big numbers
c.?Operational challenges– Lack of authentic mechanism to gather, collate and analyse within state machinery. How much garbage needs to be collected at what frequency and seasonal adjustment need to be accounted for.
d.?Categorisation – Hazardous waste, non-biodegradable, perishable, electronic waste needs to be labelled, separated and collected.
2.?Parameters (influencing factors) – The data needs to be treated with help of various parameters
a. Lack of use of Technology – Economic compulsions play major role in applying of technology or not applying it. Its does cost to apply, maintain and upgrade such technology. Semi-Automated trucks vs manual collection is classic examples.
b.?Literacy Growth – General Population becoming aware of importance & responding to systematic Garbage Collection.
c.??Poor Participation and Negligence by ‘common man’ – Awareness and participation is not going hand in hand. Segregation of Garbage, Storage and hygiene is yet to be practised widely.
3.??Variances – Regional, local factors will dominate data, parameters and outcome of the solution.
4.??End Game – Once we establish a model
a.?To predict the Garbage Collection patterns
b.?Embed variances and define come up with various if-else scenarios
Then the question is can AI model be developed to train itself using the above mentioned ingredients and come up with ‘if-else’ scenarios to ‘Predict the frequency/volume of Garbage to be collected in various demographic diverse seetings’?
Please share your valuable thoughts.
HR Analytics and Digitisation Curriculum champion @ Kingston University | PhD in HR and Employee Relations
4 天前This is AI for social good in the true sense.
Global Programme Leader | Digital Transformation | Cybersecurity | Automation and Artificial Intelligence.
4 天前Great post highlighting the various factors contributing to the challenges in garbage collection. It's interesting to see how demographic diversity, lack of technology, operational challenges, and literacy growth all play a role in this issue. I agree that a localized approach is key, as urban and rural areas have different needs when it comes to waste management.
Digital Technology Transformation Consulting, Cloud Migration, FinOps DevOps transformation, Design-led thinking leader and Lead Product Owner for asset led consulting, Partnership and alliances lead
4 天前Ravi , you touched upon almost facets of ai adoption challenges , keep writing