IoT-Based Smart Garbage System for Efficient Food Waste Management

Insung Hong, Sunghoi Park, Sunghoi Park, Beomseok Lee, Jae-Keun Lee, Daebeom Jeong, Sehyun Park, Sehyun Park

The Scientific World JOURNAL · 2014 · 242 citations · 13 references

DOIFull text

Open access

Concepts

TL;DR

The growing adoption of IoT has spurred research across many domains, with waste management emerging as a key application area where inefficient practices cause significant environmental and cost problems. This paper proposes an IoT‑based smart garbage system (SGS) to reduce food waste. SGS employs battery‑powered smart garbage bins that communicate via wireless mesh, with a router and server collecting data; it incorporates energy‑efficient stand‑alone and cooperation‑based operations to extend battery life and enhance user convenience, and was piloted for one year in Seoul's Gangnam district. The pilot experiment demonstrated a 33 % reduction in average food waste.

Abstract

Owing to a paradigm shift toward Internet of Things (IoT), researches into IoT services have been conducted in a wide range of fields. As a major application field of IoT, waste management has become one such issue. The absence of efficient waste management has caused serious environmental problems and cost issues. Therefore, in this paper, an IoT-based smart garbage system (SGS) is proposed to reduce the amount of food waste. In an SGS, battery-based smart garbage bins (SGBs) exchange information with each other using wireless mesh networks, and a router and server collect and analyze the information for service provisioning. Furthermore, the SGS includes various IoT techniques considering user convenience and increases the battery lifetime through two types of energy-efficient operations of the SGBs: stand-alone operation and cooperation-based operation. The proposed SGS had been operated as a pilot project in Gangnam district, Seoul, Republic of Korea, for a one-year period. The experiment showed that the average amount of food waste could be reduced by 33%.

References

13