Project Overview
Project Summary:
Shareat is an AI-powered solution designed to reduce food waste in single-person
households by recommending recipes and enabling local ingredient sharing. By
analyzing users' fridge contents, preferences, and expiration dates, Shareat suggests
multiple options to either buy missing ingredients, sell surplus items, or cook with what’s
available. Through a local community-based short delivery system and smart
transaction platform, users can exchange ingredients within nearby residences using
temperature-controlled ShareBoxes. The goal is to create a cost-efficient, personalized
solution that reduces household food waste, generates side income, and fosters a
sustainable community network.
Identifying the Challenge
The Social Problem:
Globally, 20% of food produced ends up as waste, equating to the mass of over 1,400
Lotte World Towers annually. Korea and Japan, where single-person households are
increasing rapidly, show especially high levels of household food waste. A survey of 31
students revealed that 77.4% had difficulty handling leftover ingredients, and 67.7%
discarded surplus food. In these countries, over 60% of food waste occurs in homes, and
62.9% of that is from single-person households. The root issue lies in surplus purchases
and the difficulty of managing small portions. This challenge calls for an efficient,
accessible way to utilize leftover food while connecting neighbors through microtransactions.
Innovation and Uniqueness
Why Our Project Stands Out:
Shareat proposes a new approach to food waste reduction by combining recipe
recommendation with local ingredient exchange. We plan to develop an algorithm that
considers individual preferences, distance, and cost, based on a large-scale dataset of
over 1 million recipe-ingredient pairs. To address safety concerns, we also plan to
incorporate AI vision technologies found in smart refrigerators and user review systems.
Additionally, our envisioned short-distance delivery model leverages idle delivery riders
to ensure efficient and eco-friendly logistics. Shareat’s strength lies in its aim to deliver a
hyper-local, personalized, and transaction-enabled platform for everyday food sharing.
Insights and Development
Learning Journey:
During the project, we gained insights into the food habits of single-person
households, particularly their difficulties in storing and managing leftover ingredients.
Interviews revealed both practical and emotional barriers to meal planning. We learned
that hyper-localized, culturally tailored systems are essential when designing
sustainable solutions for different societies.
Development Process:
Our development process is still ongoing. We began with surveys and interviews to
identify key pain points such as surplus food and delivery costs. We created an initial
prototype and simulated how ShareBoxes and short-range delivery might function.
Although the technologies are under planning and prototyping stages, we envision
incorporating vision-based verification and rating systems to ensure trust and safety. The
collaborative work between Korean and Japanese team members has enriched our
development with diverse perspectives.
