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❯AI-Based Solid Waste Classification
Large Companies
Small Companies
Entertainment and Media - Metadata Tagging
For:
Digital asset managers.
Scope:
Realizing the value of historical sporting digital media assets by using Artificial Intelligence (AI) to assist in doing the work of 15 interns.
Goal:
Improved Product Development / R&D, Improve Operation Efficiency
AI-Based Solid Waste Classification
For:
Government Municipal Corporations, Solid Waste Management Companies
Education - Automated Content Generators
For:
Online course creators.
Scope:
Intelligently generate, curate, and recommend content educational content.
Goal:
Improved Customer Experience
Crop Diagnosis & Product Recommendations Through AI
For:
Farmers, Biochemical companies, Crop disease treatment manufacturers
Goal:
Improved Product Development / R&D, Improve Operation Efficiency
Other
Computer Vision - Image Segmentation
For:
Farmers
Scope:
Using image processing to implement a livestock monitoring application.
Goal:
Improved Operation
Disaster and Emergency Prediction & Impact Model
For:
National-level disaster management professionals, Climate change adaptation experts, Government agencies, At-risk communities
General Public
Healthcare - Improve Investigatory Work
For:
Radiologists
Scope:
Using machine learning to predict lung cancer from CT scans.
Goal:
Anticipate Risks
Prediction of Multidrug-Resistant TB from CT Pulmonary Images Based on Deep Learning Techniques
For:
Clinicians and medical professionals predicting multidrug-resistant (MDR) patients from drug-sensitive (DS) ones based on CT lung images.
Goal:
Improved Employee Efficiency
General Public
Education - Smart Learning Content
For:
Online course creators and online learners.
Scope:
Empowering course creators to focus on complex decision-making and creativity with Computer Vision and Natural Language Processing.
Goal:
Improved Employee Efficiency
Autonomous Robot Improves Surgical Precision Using AI
For:
Hospitals using Autonomous robotic surgery via the STAR system
Goal:
Improve Operation Efficiency
Disaster and Emergency Prediction & Impact Model
For:
National-level disaster management professionals, Climate change adaptation experts, Government agencies, At-risk communities.
Large Companies
Small Companies
Accounting and Finance - Automate Invoices and Expense Management
For:
Financial Controllers
Scope:
Using Image Processing and Optical Character Recognition to create operational efficiencies through automation of expense approval and reconciliation workflows.
Goal:
Improved Employee Efficiency
AI-Based Solid Waste Classification
For:
Government Municipal Corporations, Solid Waste Management Companies
Problem addressed
Urban environments in most countries today are struggling with the collection and management of municipal solid waste (MSW). First of all, after collecting waste, it is a big challenge to classify the MSW mix that includes yard waste, food waste, plastics, wood, metals, papers, rubber, leather, batteries, inert materials, textiles, paint containers, and many other things.
The main obstacle to sorting is the variety of such generated solid waste. These wastes must first be properly fractionated and sorted before going through any significant treatment procedures.
Solutions for MSW classification must be technically practical, economically viable, socially and legally acceptable, and environmentally friendly.
Description
An AI-based solid waste classification system is developed for the segregation of solid waste. This system uses waste bins equipped with sensors to keep the level of waste in the bins.
Secondly, a camera is deployed to take a picture of the trash dump which contains multiple waste items. The image is segmented into grids using a grid segmentation method. This image is fed into a trained deep-learning algorithm to carry out identification. A classifier further assesses the class of each waste object and the segregated waste item is managed with the help of the control unit.
The central component of the entire system is the control unit. Based on the information obtained from the edge processing module, it produces control signals. It regulates the robotic arm's motion in accordance with the degree of freedom specifications. Using this robotic arm, the system separates the item into the appropriate garbage container i.e., metal, plastic, glass, trash, etc.
This AI-based solid waste classification system provides awe-inspiring segmentation results. The deep-learning algorithm, a popular choice for image classification, gives us 96% accurate results.
Image
AI: Perceive
Machine Learning
AI: Understand
Automate Process
AI: Act