Automate
❯
Automate Process
❯AI-Based Solid Waste Classification
Large Companies
NLP - Text summarization
For:
Media Intelligence Analysts
Scope:
Using Abstractive Text Summarization to reduce analysis costs for media monitoring.
Goal:
Improve Operation Efficiency
Intelligent Document Processing Using AI
For:
Government & public entities
Government departments
AI-Based Solid Waste Classification
For:
Government Municipal Corporations, Solid Waste Management Companies
Large Companies
Small Companies
Entertainment and Media - Subtitle Creation
For:
Content creators
Scope:
Creating efficiencies for content creators via automatic subtitle creation for social video.
Goal:
Improved Employee Efficiency
Large Companies
Small Companies
Improve Business Decision
For:
Credit controllers
Scope:
Using Machine Learning to automate the assessment of creditworthiness for loan applicants at a bank.
Goal:
Improve Operation Efficiency, Increase Revenues
Intelligent Social Listening
For:
Local authorities, Government agencies
Automated Quality Assurance
For:
Quality Engineers
Large Companies
NLP - Machine translation
For:
Translation Managers and Translators.
Scope:
Using Machine Translation to scale content production and create a more streamlined and efficient translation process.
Goal:
Improve Operation Efficiency, Automate a Business Process
Procurement - Cost Analysis
For:
VP Global Supply Chain Management, Category Managers
Scope:
Realizing operational efficiencies and working capital improvements through automated spend classification.
Goal:
Reduce costs, Improved Employee Efficiency
How ML Can Improve Churn Prediction to Retain More Revenue for Insurers
For:
Portfolio Managers
Customer Retention
Goal:
Improved Operation
From Weeks Down to Hours: How insurers innovate with AI to shorten claims processing time and improve customer experience
For:
- Claims Management
- Customer Experience.
Goal:
Improved Customer Experience
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
Large Companies
Accounting and Finance - Improve Profitability Reports
For:
Financial analysts
Scope:
Using Natural Language Generation to automate the production of commentary on profit and loss statements at a bank.
Goal:
Improved Employee Efficiency, Improve Operation Efficiency
Large Companies
Audio Signal Processing - Voice to text Conversion
For:
Lawyers and Judges
Scope:
Using Automatic Speech Recognition (ASR) to transcribe court case proceedings.
Goal:
Automate a Business Process
Precision Farming as a Service
For:
Farmers
Scope:
Use visual recognition to identify and help fight parasites attacking organic farms.
Goal:
Anticipate Risks, Improve Operation Efficiency
Autonomous Robot Improves Surgical Precision Using AI
For:
Hospitals using Autonomous robotic surgery via the STAR system
Goal:
Improve Operation Efficiency
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