Improve Smart Waste Management to Preserve Tourist Attractions Yogyakarta in IoT Environment

Arinta, Rania Rizki; Watomakin, Dominikus Boli; Suyoto, Suyoto

doi:10.1109/icosta48221.2020.1570610836

Cited by 4 publications

(1 citation statement)

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“…Improve smart waste management to preserve tourist attractions in Yogyakarta in IoT Environment was created [24], the system provides sensors to monitor the dustbins status, two categories of the dustbins, one for the wet waste, and another for the dry waste, there are three servos, every dustbin has servo is attached to its lid, and one to carry the waste to its category dustbin. All the servos are working according to the output of the moisture sensor.…”

Section: Figure 2 Circuit Diagram Of the Smart Bin [16]mentioning

confidence: 99%

Smart bin monitoring system for smart waste management

Ahmed

Akkad

Rima

2020

MDT

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The fourth industrial revolution offers new technologies and solutions to increase efficiency, availability, flexibility, and decrease the economical footprint of manufacturing and service processes. In smart cities, a wide range of Industry 4.0 technologies can be used in the field of road traffic monitoring, health monitoring, and many operations, like the municipal waste collection. Internet of Things makes it possible to reduce the required material handling solutions of municipal waste collection, like loading and unloading, transportation, and warehousing. With smart waste management, no need for trucks to come every day and check every single dustbin if it is full or not as in the traditional situation, therefore the human power, time, cost, and spreading of toxic gas will be reduced. The amounts of the garbage will be monitored by sensors, pollution level by moisture sensor, and an odor sensor. The collected data can also be used to find the optimal path for the truck’s drivers. Within the frame of this article, the authors describe an on-line smart bin monitoring system.

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Section: Figure 2 Circuit Diagram Of the Smart Bin [16]mentioning

confidence: 99%