International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
Agricultural Waste to Wealth: Smart Garbage Collection and ML-Based Incentive System for Rural Sustainability
Donda Hasti1 , Jasoliya Srushti2 , Reena Desai3
1Student,Dept.of computer Application,GMIU,Bhavnagar,Gujarat
2Student,Dept.of computer Application,GMIU,Bhavnagar,Gujarat
3Professor,Dept. of computer Application,GMIU,Bhavnagar,Gujarat
Abstract - Managing agricultural waste is a challenge that many rural communities encounter daily. Traditional methods like open burning or dumping are still common, but they harm the environment and waste valuable materials. To make a real difference, we must rethink our approach. We should turn to smarter, technology-driven solutions that everyone can easily access.This paper presents a new framework that turns agricultural waste into economic value by using modern technologies. The proposed system combines Internet of Things (IoT) devices with machine learning (ML) techniques to monitor waste, classify it efficiently, and reward users for responsible disposal. A smart garbage collection unit equipped with sensors measures both the type and amount of waste. An intelligent reward system provides financial incentives to users.We designed this system for both local governments and private groups, making it usable almost anywhere. By rewarding environmentalcare, wehopetoencouragemore people to get involved and help build a more sustainable future in rural areas. It aims to ensure everyone benefits while taking care of the planet
Key Words: Agricultural Waste, Smart Waste Management, Internet of Things, Machine Learning, Incentive System, Rural Sustainability, Circular Economy
1. INTRODUCTION
1.1
Background
The agricultural industry contributes to the economic development, while agricultural waste, such as crop waste, organic waste, and plastic materials such as fertilizerpackages,isanenvironmentalchallengesince they are improperly managed and disposed. Poor infrastructure in rural communities has led to lack of wastemanagementintheareaswherefarmersdispose andevenburntheirwastematerialsanywheretheysee fit. It is a threat to the environment, for example, air pollutionanddecreasedsoilfertility.Also,theproblem overlookstheimportanceofagriculturalwasteinterms ofeconomy.IntroductionofIoTandmachinelearninghas broughtaboutadifferentapproachtowastemanagement andmakesthemanagementofagriculturalwastesimple. Incentiveprogramsandautomationwillbeconsideredin themanagementprocess.
1.2 Problem Statement
Evenwithtechnologicalprogress,wastemanagementin ruralareasstillfacesmanychallenges:
- No structured and organized waste collection systems
- Lackoffinancialincentivesforfarmerstomanage wasteresponsibly
-Limitedawarenessandpracticeofproperwaste sorting.
-Noreal-timemonitoring ordata-driven decisionmaking.
1.3 Objectives
Projectobjectivesare:
- Development of a garbage collection system throughwasteidentification
- Incorporatingsafetyfeaturesinthesystemsuch asloginandlogoutoptions
- Machine learning in waste classification and incentivescomputation
-Developingasystemthatcanbeutilizedbyboththe governmentandtheprivatesector
Facilitatingfarmers’meansofgeneratingincomefromwaste producedinagriculture
2. LITERATURE REVIEW
Inrecenttimes,studieshavebeenconductedonhow touseIoTalongwithartificialintelligenceinenhancing thewastemanagementsystem.Withsmartbins,sensors will determine the level of waste collected and enable efficientwastecollection.Themachinelearningprocess enables accurate sorting of different forms of waste. However, the solutions provided are mostly based on urbanenvironmentsandnotintheruralenvironment. There is no incentive system provided hence reduced userinvolvement.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
Table -1: ComparisonofExistingSmartWaste ManagementSystem
System Type Technology Used Advantage Limitation
IoTWaste Monitoring IoTSensors Real-time tracking Noincentive mechanism
ML-Based Classification AIModels Accurate sorting High computational cost
Smart Agriculture Systems IoT+AI Automation Notfocused onwaste
Blockchain Waste Systems Blockchain+ ML Transparency Complex implementation
3. PROPOSED METHODOLOGY
Theproposedsystembringstogetherseveralcomponents tocreateasmoothwastemanagementprocess:
-A smart garbage collection unit with a unique identificationnumber
-Asecureloginandlogoutsystemforusers
-Sensors to measure waste weight and detect its type
-A machine learning model for classification and rewardcalculation
-Acloud-based platform forstoringandanalyzing collecteddata.
3.1 System Workflow
Step 1: Registration
Users register through a mobile app and receive a uniqueID.
Step 2: Login
Users access the system securely using their credentials.
Step 3: Waste Disposal
Usersdepositwasteintothesmartunit,wheresensors capturedatasuchasweightandcategory.
Step 4: Processing
The machine learning model analyzes the data to determinetheclassificationandreward.
Step5:Reward Distribution
Incentivesarecrediteddirectlytotheuser’sdigitalwallet orbankaccount.
Step 6:Log out
The session ends securely after the transaction is completed.
[Figure1: systemWorkflow]
4. ANALYSIS AND DISCUSSION
4.1Incentive-Based Model
Akeyfeatureoftheproposedsystemisitsrewardbasedapproach.Byofferingfinancialbenefitsforproper wastedisposal,thissystemmotivatesuserstoparticipate actively. This not only improves waste collection efficiency but also encourages environmentally responsiblebehavior.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
Table 2: Incentive Structure
Waste Type Example Rate (per kg) Reward
WetWaste Food,cropresidue ₹8/kg Low
DryWaste Paper,Cartonboxes ₹10/kg Medium
Plastic Waste Fertilizerbags,plastic bottal ₹12/kg High
4.2Stakeholder Benefits
Table3: StakeholderBenefits of Smart Waste Management System
Stakeholder Benefits
Farmers Earn additional income and easy waste disposal
Government Better monitoring and data-driven decisions
Private Companies Revenuethroughrecyclingprocesses
Environment Reduced pollution and improved sustainability
4.3 Role of Government and Private Sector GovernmentRole:
- Developinfrastructure
- Implementregulationsandpolicies
- Promoteawarenessprograms
- Providefinancialassistance
Private Sector Role:
- Designandmaintainthesystem.
- Deploysmartcollectionunits
- Managedataandanalytics.
- Generaterevenuethroughrecyclingoperations
5. CHALLENGES /LIMITATIONS
Technical Issues
- Dependenceonstableinternetconnectivity.
- Needforregularmaintenance
- Highsetupandinstallationcosts.
Social Issues
- Limitedawarenessinruralcommunities.
- Resistancetoadoptingnewtechnologies
- Needfortrainingandeducation
Operational Issues
- Difficultyinmaintainingproperwasteseparation
- Ensuringsystemreliability
- Managinglargevolumesofdata.
Security Concerns
- Protectinguserdata
- Risksfromcyberthreats.
- Securehandlingoffinancialtransactions.
Economic Limitations
- Balancingrewardsandprofits
- Ensuringlong-termsustainability
- Highinitialinvestment
6. FUTURE DIRECTIONS
Thesystemcanimprovefurtherby
-Integratingblockchaintechnologyfortransparency
-ImplementingdynamicpricingusingadvancedAI models.
-Expandingintosmartvillageecosystems
-Introducingcarboncredit-basedincentives
-Usingedgecomputingforofflinefunctionality
-Extending the system to manage industrial and electronicwaste.
7. CONCLUSIONS
This paper presents a practical and forward-thinking approachtomanagingagriculturalwastebycombining IoT, machine learning, and incentive-based strategies. The proposed system turns waste into a valuable resource, creating both environmental and economic benefits.By encouraging responsible behavior through financial rewards; the model ensures active user participation and long-term sustainability. It offers benefits to all stakeholders, including farmers, government bodies, private organizations, and the environment.Withproperimplementationandsupport, this system has the potential to improve rural waste management practices significantly and contribute to developingasustainableandcirculareconomy.
International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056
Volume: 13 Issue: 05 | May 2026 www.irjet.net p-ISSN: 2395-0072
8. REFERENCES
[1] Authoret al.,“MachineLearningforSustainableWaste TreatmentandCircularEconomy,”NatureReviews,vol. XX,2024.[Online].Available:https://www.nature.com/ar ticles/s44296-024-000099https://www.mdpi.com/2785860
[2] MDPI, “AI in Smart Agriculture,” 2024. Available: https://www.mdpi.com/2078-2489/16/2/100
[3] Authoretal.,“SmartWasteManagementSystemUsing MachineLearningandBigDataAnalytics,”International Journal of Engineering Sciences, 2023. [Online]. Available:https://theaspd.com/index.php/ijes/article/vi ew/2357
[4] IJACSA, “Smart Agricultural Management,” 2023. Available:https://thesai.org/Downloads/Volume14No7 /Paper_107Smart_Agri_A_Smart_Agricultural_Management.pdf
[5] IJSRED, “Smart Waste Management using ML,” 2025. Available:https://ijsred.com/volume8/issue3/IJSREDV8I3P613.pdf
[6] ScienceDirect,“IoTWasteManagementSystem,”2024. Available:https://www.sciencedirect.com/science/article /pii/S0167739X24001183
[7] ResearchGate,“SmartWasteusingIoT,”2023.Available: https://www.researchgate.net/publication/366170794
[8] IJISAE,“Agricultural Waste Management,” 2024. Available:https://www.ijisae.org/index.php/IJISAE/artic le/view/4613
[9] JSRR, “Smart Agriculture Study,” 2024. Available: https://journaljsrr.com/index.php/JSRR/article/view/37 56
[10] arXiv, “Smart Village IoT,” 2021. Available: https://arxiv.org/abs/2106.03750
[11] ResearchGate, “AI Waste Management,” 2025. Available: https://www.researchgate.net/publication/389490649
[12] IJERT, “Smart Waste Management System,” 2023. Available: https://www.ijert.org/smart-wastemanagement-system-using-iot
[13] arXiv, “IoT for Sustainable Agriculture,” 2022. Available:https://arxiv.org/abs/2206.06300
[14] V. K. Singh and R. Mehta, “Intelligent Agricultural WasteRecyclingSystemUsingIoTandAI,”Computers andElectronicsinAgriculture,vol.189,2021.[Online]. Available:
https://www.sciencedirect.com/science/article/pii/S01 68169921003456