Demo Day | Solving Real-World Problems Through Community-Driven Artificial Intelligence

Demo Day | Solving Real-World Problems Through Community-Driven Artificial Intelligence

Omdena Demo Day

Solving High-Impact Challenges Through Community-Driven Artificial Intelligence

June 8th 2022, 4 pm UTC

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Judges

Michael Tjalve

Michael Tjalve

Director of Innovation, Tech for Social Impact at Microsoft Philanthropies

Alexander Díaz

Alexander Díaz

AI for Social Good & Crisis Response at Google.org

Ashish S.

Ashish S.

Head of AI/ML Strategy and Business Development at AWS

Omar Mohsine

Omar Mohsine

Open Source Coordinator and former Deputy Head UN Technology Innovation Lab

Featured Solutions

Water Quality Monitoring Dashboard for Kutch Region

Monitoring Water Quality in Western India

Q

Monitoring Water Quality in Western India

This project is to develop a centralized dashboard with different water quality parameters for analysing, interpretation, and visualization in near real-time using Remote Sensing and AI for better decision making. By developing a dashboard, decision-makers can easily identify if any parameter is not within the standard limits then immediate action can be taken for water treatment. This dashboard will reinforce the ability to monitor water quality more effectively and efficiently.

SDG 6: Clean Water and Sanitation
Political Fake News Detection

Detecting Political Fake News and Misinformation (LATAM)

Q

Detecting Political Fake News and Misinformation (LATAM)

This project is to detect anomalies in the news, where the results of the project can provide further support for both private and public companies on their future analysis and activities to combat misinformation. Additionally, researchers and students could use the outcomes for their own research or use it for learning purposes.

SDG 16: Peace, Justice, and Strong Institutions
Mental Health Chatbot

Developing an AI-driven & Secure Online Marketplace in Bangladesh

Q

Developing an AI-driven & Secure Online Marketplace in Bangladesh

With a higher economic growth rate in South Asia, Bangladesh has been fruitful in the e-commerce business. The rise of online users has caught fraud businesses. To solve this the chapter has targeted securing the marketplace with AI. The good collaborative performance has created a recommender system with customer service reviews from various popular e-commerce. The service provides a recommendation of products based on the quality and service review. The team has embraced web-scraping, data analysis, natural language processing, recommender system, and AWS cloud deployment.

SDG 8: Decent Work and Economic Growth 
Increasing Renewable Energy Access in Philippines

Finding Safe Paths During Natural Disasters in Japan

Q

Finding Paths to Safety Following Natural Disasters in Japan

Natural Disasters is a serious threat in Japan though it has well-developed disaster response systems, but densely populated cities and narrow roads make managing the response difficult. By giving individuals information about the secure route from their homes and places of work, it will increase their awareness of their surroundings and enhance their preparedness.An Interactive Application to devise the safest path in Nakagawa-Ku region, Japan during natural disasters like Earthquakes, Tsunamis and Floods that helps in prioritizing the citizens safety in risk prone zones.

SDG 9 & 11: Innovation and Infrastructure; Sustainable Cities
Detect Plant Disease

Hyderabad, India Chapter – Text-based Healthcare Chatbot Supporting Admitted Patients

Q

Hyderabad, India Chapter – Text-based Healthcare Chatbot Supporting Admitted Patients

Currently, in our healthcare system, the patients often face anxiety and nervousness while waiting for the test results and health checkups and they feel paranoid due to several doubts arising in their minds regarding post-treatment complications and actions. This epidemical surge of Covid has projected out the extreme levels that add the pointer to a shortage of doctors, caregivers, nurses, and other medical staff to pay attention to these admitted patients and set out priorities based on medical conditions.

This project focuses on assisting patients by providing general information about their health-related questions and ultimately helps doctors to attend more emergency cases simultaneously. The medical staff and healthcare management can provide a pleasing experience for patients by incorporating preliminary forms in the chatbot itself containing patients’ general information whenever he or she visits the hospital.This chatbot also has the potential to emerge as an engaging tool for the patients and their immediate families by shaping it more robustly and spreading needed awareness effectively using customization.

SDG 3: Good Health and Well Being
Detect Plant Disease

Omdena K-12 Chapter - Using Machine Learning to Reduce Food Waste

Q

Omdena K-12 Chapter - Using Machine Learning to Reduce Food Waste

In India, 23 million tonnes of food cereals, 12 million tonnes of fruits, and 21 million tonnes of vegetables are lost each year, with a total estimated value of 240 billion Rupees. A recent estimate by the Ministry of Food Processing is that agricultural produce worth 580 billion Rupees is wasted in India each year! Due to the lack of knowing whether they can donate food and knowledge of donation centers, people end up throwing their leftover food. 

Our Solution for Demo – An app named “Perishably”, which has the following key features:

• An AI-based app that predicts the expiry of fruits

• The user can manage his/her food better, thus reducing wastage

• The user has an option to locate nearby donation centers, to donate leftover food

SDG 2: Zero Hunger
SDGs

Taking an AI-Enabled Approach To the SDG Commitments

& 10x our impact with the global AI community

More Omdena projects connected to the SDGs

Computer Vision

Identifying Malnutrition of Children Through Computer Vision

Remote Sensing

Improving Food Security and Crop Yield in Senegal Using Satellite Imagery

Natural Language Processing

Identifying & Monitoring Human Rights Abuses Through NLP Language Models

Data Preparation & Digitization

Improving Case Management for Cross-Border Child Protection

Machine Learning

Preventing the Financing of Terrorism Using Machine Learning

Omdena recruited a team of more than 50 data scientists around the globe who worked tirelessly over the entire project duration. I´ve rarely seen a team working so hard for a common goal and achieving such tangible results in a short period of time. The project resulted in several outcomes that are extremely promising, not just for Save the Children, but for the entire field of NGOs and other actors in the field.

John Zoltner

Senior Advisor of Technology for Development and Innovation, Save the Children

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Omdena | Building AI Solutions for Real-World Problems