Smart Trash Bin Research Articles

PENGARUH PENGGUNAAN ALAT PERAGA SMART TRASH BIN TERHADAP PEMAHAMAN KONSEP FISIKA MATERI TEKNOLOGI DIGITAL

Pengaruh Penggunaan Alat Peraga Smart Trash Bin Terhadap Pemahaman Konsep Fisika Materi Teknologi Digital. The purpose of this study is to determine the understanding of the concept of digital technology classes taught and not taught using smart trash bin props, knowing the difference in understanding the concept of digital technology classes taught and not taught using smart trash bin props. The type of research is experimental with a posttest-only control design. The instrument used tests the understanding of concepts. Data analysis techniques use descriptive and inferential analysis. The average score of concept comprehension test results in classes taught using smart trash bin props was 80.42, with a very high category, while in classes that were not taught using smart trash bin props, it was 76.04, with a high category. The average value of the concept understanding test results taught with smart trash bin props is greater than the average value of the concept understanding test results that are not taught using smart trash bin props, so it can be concluded that the use of smart trash bin tools has a positive influence on the understanding of the concept of digital technology material. Meanwhile, the results of hypothetical testing obtained a significant value of 0.194 > 0.05, meaning that there was no significant difference in understanding of concepts between classes taught and not taught using smart trash bin props.

Rancang Bangun Smart Trash Bin Automation pada Smartlab Politeknik Negeri Jakarta

Smartlab is a new laboratory in Department of Electrical Engineering, Jakarta State Polytechnic. The lab is designed to support the latest research in the telecommunications field, including the implementation of automation for the systems and items in the lab. The development of a Smart Trash Bin Automation is one of the ongoing projects. Using information and digital technology, it aids in the management and handling of waste collection. This research has created the Smart Trash Bin Automation system, which is connected to the internet using Arduino Uno Rev3 and ESP-32. This module is responsible for processing and sending data from the trash bins to a smartphone. The smartphone use Blynk application, which receives data when the systems sends notification to the users when the trash bin reaches its maximum capacity. Smart Trash Bin Automation is also equipped with an ultrasonic sensor that detects objects inside the trash bin. If an object is detected, the trash bin will open automatically, eliminating the need for users to touch the trash bin directly. The system has been tested successfully, with all devices functioting as intended.
 Keywords—Arduino, ESP-32, Smartlab, Smart Trash Bin Automation, Ultrasonic sensor.

Smart Trash Bin to Prevent Animal Disturbance Using Raspberry Pi and Deep Learning

A trash can is an indispensable component of human daily life. It is ubiquitous and extremely useful for keeping the city clean. However, littering is a frequent and widespread problem. Not only do humans litter, but so do animals, particularly monkeys. Animals are constantly searching for food, and when we discard our food waste, they are attracted and leave their natural habitats. Following that, the user may forget to lock the trash can, which may end up in the hands of the animal. With the aid of a deep learning system that detects and identifies human subjects, a smart trash bin with an autonomous locking mechanism will be used in this project to reduce animal disturbance. In this paper, Raspberry-Pi 4 module is being used. Moreover, this article describes a human subject identification method and its real-time displacement using the OpenCV library of programming roles, which is primarily aimed at Raspberry Pi with camera module. The smart trash bin system helps to reduce animal disturbance and minimise littering.

Time dependent performance analysis of a Smart Trash bin using state-based Markov model and Reliability approach

In this paper, the authors have developed a quantitative mathematical model to assess the performance of a smart trash bin. This model takes into account six hardware components of the trash bin, including Arduino Uno, ultrasonic sensor, servo motor, switch, battery, jumper wires utilizing Markov modelling and reliability-based approach. The objective of this model is to facilitate timely planning of repair and maintenance activities, ensuring prolonged availability of the smart trash bin after identifying the weakest component/components of the system.The efficient functioning of all components in the smart trash bin is imperative for the timely transmission of the garbage level data to the municipal corporation. To achieve this, the paper focuses on evaluating key reliability metric for smart trash bin system, specifically reliability, unreliability, and Mean time to Failure (MTTF). The modelling approach employs a state-based Markov model, from which Kolmogorov differential equations are derived and subsequently solved using Laplace transformation. After collecting data from organization and experts of the field explicit expression for system reliability, unreliability and MTTF have been obtained.Furthermore, this study includes sensitivity analysis of the system to pinpoint critical components which is switch and servo motor, requiring attention for proper maintenance. The research finding indicates that reliability and MTTF of the system diminish as the failure rate of the components increase under certain conditions.

TEMPAT SAMPAH PINTAR “MYSMARTRECYLEBIN” BERBASIS TEKNOLOGI INTERNET OF THINGS (IOT) DAN BIG DATA

This research aims to develop "MySmartRecyleBin," a smart trash bin that utilizes Internet of Things (IoT) technology and Big Data in many cities around the world that face serious challenges in waste management. This research was conducted to face the urgency of handling the increasingly pressing waste problem. The aim is to help governments and waste managers overcome waste management challenges in a more sustainable manner, reduce waste management costs, and strengthen waste management systems. This research involves researchers and developers of IoT and Big Data technology collaborating to create a smarter and more efficient waste management system. By utilizing IoT and Big Data technology, this research produces a system that allows real-time data collection from various devices connected to the internet, such as sensors on trash cans and waste transport fleets. This data is then analyzed to understand user behavior and waste collection patterns. Through this technology, the waste management system can become more effective and efficient. This technology uses a Microcontroller, Load Cell, RFID Tag, and RestFull API Technology as a communication medium to the Waste Management Information System (MySipah). The test results show the success of sending data over the last 1 year, namely January 2022 is 152 kg, February 2022 is 109 kg, March 2022 is 93 kg, April 2022 is 113 kg, May 2022 is 126 kg, June 2022 is 161 kg, July 2022 is 188 kg, August 2022 is 143 kg, September 2022 is 102 kg, October 2022 is 113 kg, November 2022 is 116 kg, December 2022 is 124 kg.

Upaya Peningkatan Sikap Peduli Lingkungan Melalui Kegiatan Ekstrakurikuler Robotik di MTSN 3 Pekanbaru

MTSN 3 Pekanbaru is a school that has a mission of "Character, Excellence and Environmental Insight". One of its missions is to develop students' interest in talent through superior robotics, research, academic and tahfiz class programs. And another vision is to develop awareness and love for the environment through environmental care activities. Based on this mission and vision, an effort is needed to provide knowledge about environmental care attitudes to students in an interesting way, one of which is robotic extracurricular activities by making smart trash can robots (Smart Trash Bin). Based on the existing problems, the solutions provided consist of 1) Socialization regarding environmental care attitudes. 2) training on waste management. 3) Workshop on making intelligent trash can robots (Smart Trash Bin). The method of implementing the activities are 1) the preparation stage, 2) the implementation stage, 3) the evaluation and reporting stage. The results obtained are that students are able to explain the difference between waste and how to manage it and are also able to make smart trash cans.

Smart Trash Bin for Management of Garbage Problem in Society

Along with the times, one of the environmental problems faced today is the waste problem. Every day humans will produce waste, both industrial waste and household waste in everyday life. Garbage will become an environmental problem because it can interfere with human health, cause bad smells and even air pollution. Poor waste management causes harmful and unhealthy environmental problems. Sometimes people are reluctant when they want to dispose of garbage by opening and closing the trash can so it is feared that they will get bacteria on their hands. The problem of environmental waste can arise from waste management that unites all types of organic and inorganic waste in the same place, making it difficult to recycle waste. Another problem is that sometimes the cleaners are negligent in emptying the full trash can, so it will cause a bad smell. Based on the above problems, it is necessary to make a smart trash bin which will later be able to sort out the types of organic and inorganic waste. The lid of the trash can will open automatically when someone wants to throw out the trash and it will close automatically when it's finished taking out the trash. With the waste sorting technology, it will automatically reduce environmental pollution by waste, and facilitate waste management so that it can be recycled again. To overcome the bins that are full for too long, if the trash is full, it will automatically notify the cleaners via Telegram messages. From the test results, it can be concluded that the ultrasonic sensor can detect if someone is approaching with a maximum distance of 50 cm so that the cover can be opened automatically for 7 seconds. The servo motor can rotate the waste sorter according to the type of organic or inorganic waste based on the detection results of the capacitive proximity sensor. The telegram message has been successfully sent if the garbage condition has been fully detected through the ultrasonic sensor. LCD can display the type of organic or inorganic waste accurately.

Smart Trash with Web Integrated Volume Monitoring and Sorting System via MQTT Protocol

The increasing human population makes each year its production increase significantly. People's ignorance to separate the types of waste has triggered various disasters. Many studies have aimed at tackling this problem, such as smart trash bins that can sort various types of organic and inorganic materials and detect waste. However, it can products with many functions are not all integrated into one product. Purpose of this research is to provide a product that can integrate various smart trash bin functions with a volume monitoring system and sorting metal, non-metal, and organic waste types monitored via the web using the MQTT Protocol. This research prototype consists of several devices, namely smart trash bin equipped with proximity sensors, capacitive proximity sensors, and infrared sensors. In addition, this system is equipped with an ultrasonic sensor to detect the height of the trash. The Wi-Fi module integrated this system with web applications and the MQTT protocol. Based on the test, the system has been running well since the sensor data collection test is 70%, the delay test from the sensor input to the actuator is 3.48 s, the ultrasonic sensor reading accuracy is 97.16%, and the throughput on the monitoring website is 5084.75 bytes/sec.

Smart trash bin level monitoring system

Solid waste management is still a big issue in cities, causing considerable health and environmental problems. Trash cans are strategically distributed across the city to handle solid waste. These containers have the potential to overflow, contaminating the environment and creating trouble for people. A real-time remote monitoring system that informs a waste management firm or the relevant authorities of the level of rubbish in trash bins is required. The proposed system describes the creation and validation of a self-powered, LoRaIoT-enabled Smart Trash Bin Level Monitoring System for effective solid waste management (IoT-STBLMS). Smart Trash Bin Level Measurement Unit (STBLMU) monitors the unfilled level and geographical position of a trash bin, then analyses and communicates the data to a cloud platform using the MQTT protocol. A dashboard allows users to examine and evaluate the status of each bin as well as its geo-location. The designed system's accuracy, average current consumption and life expectancy, battery charging time, and cost were investigated and published here.

YOLO-Based Object Detection for Separate Collection of Recyclables and Capacity Monitoring of Trash Bins

This study describes the development of a smart trash bin that separates and collects recyclables using a webcam and You Only Look Once (YOLO) real-time object detection in Raspberry Pi, to detect and classify these recyclables into their correct categories. The classification result rotates the trash bin lid and reveals the correct trash bin compartment for the user to throw away trash. The performance of the YOLO model was evaluated to measure its accuracy, which was 91% under an optimal computing environment and 75% when deployed in Raspberry Pi. Several Internet of Things hardware, such as ultrasonic sensors for measuring trash bin capacity and GPS for locating trash bin coordinates, are implemented to provide capacity monitoring controlled by Arduino Uno. The capacity and GPS information are uploaded to Firebase Database via theESP8266 Wi-Fi module. To deliver the capacity monitoring feature, the uploaded trash bin capacity information is displayed on the mobile application in the form of a bar level developed in the MIT App Inventor for the user to quickly take action if required. The system proposed in this study is intended to be implemented in a rural area, where it can potentially solve the recyclable waste separation problem.

Smart Garbage Bin Based on AIoT

Waste management and monitoring is a major concern in the context of the environment, and has a significant impact on human health. The concept of the Artificial Intelligence of Things (AIoT) can help people in everyday tasks in life. This study proposes a smart trash bin to help solve the problem of waste management and monitoring. Traditional methods of garbage disposal require human labor, and pose a hazard to the worker. The proposed smart garbage bin can move itself by using ultrasonic sensors and a web camera, which serves as its “eyes.” Because the smart garbage bin is designed for indoor use and mobility, we use a Bluetooth beacon for location tracking, whereby the bin transmits a constant signal that the other devices in the environment can detect. A smart garbage bin was developed in this study to be used in the E315 research room in the Electrical Engineering Department of the National Chin-Yi University of Technology. An Android application was also developed to help users monitor waste in the smart bin.

IoT-Based Waste Height and Weight Monitoring System

Over the past decade, the use of smart waste monitoring systems has become a popular way of waste management. This system generally makes it easier for scavengers and household users to monitor the status of the level of waste in the trash. This study aims to create an innovative IoT-based intelligent waste monitoring system to facilitate waste monitoring for households. The proposed system consists of the first 3 important parts, an IoT-based household trash bin monitoring system. Second, the smart trash can monitor system uses 2 sensors, namely ultrasonic sensors and load cell sensors. Third, display a full indicator on the web if it has reached the maximum height or weight limit of garbage. Meanwhile, the evaluation of the system is carried out by testing the accuracy of the weight and height values of the waste on the smart waste system and using the black-box method for testing application features. The proposed smart trash bin has been tested manually using a ruler for measuring the height of the trash compared to measurements using a height sensor resulting in an average gap error of 0.08 cm. While the results of the comparison of measuring waste weight using a scale in kg compared to measuring waste weight using a weight sensor resulted in an average gap error of 0.03 kg. The test results are close to the actual height and weight of the garbage. The main contribution of this research is a system to monitor the volume of waste in the trash that can be linked to the application of waste collection service management for residential environments. Smart trash can users can monitor the condition of the waste by looking at the high level and weight indicators of the waste on the web application when it reaches the maximum then sending an order message to the waste collection manager for waste.

Smart Trash Bin

The quantity of garbage in the city of Mangalore is increasing daily. The garbage needs to be gathered from several points of location and then need to be moved to garbage collection sites. These enormous number of garbage collection points itself seed pollution and also absence of waste management resources available by the government will have the severe impact on environment and surrounding community. In view of all these impacts on the community and environment the authors have lifted this issue to build an internet of things based smart trash bin in and around the city. These smart trash bins are very fruitful and time-efficient waste management system that will be effective in Mangalore's smart city project.

Intelligent waste management system using deep learning with IoT

Waste management leads to the demolition of waste conducted by recycling and landfilling. Deep learning and the Internet of things (IoT) confer an agile solution in classification and real-time data monitoring, respectively. This paper reflects a capable architecture of the waste management system based on deep learning and IoT. The proposed model renders an astute way to sort digestible and indigestible waste using a convolutional neural network (CNN), a popular deep learning paradigm. The scheme also introduces an architectural design of a smart trash bin that utilizes a microcontroller with multiple sensors. The proposed method employs IoT and Bluetooth connectivity for data monitoring. IoT enables control of real-time data from anywhere while Bluetooth aids short-range data monitoring through an android application. To examine the efficacy of the developed model, the accuracy of waste label classification, sensors data estimation, and system usability scale (SUS) are enumerated and interpreted. The classification accuracy of the proposed architecture based on the CNN model is 95.3125%, and the SUS score is 86%. However, this smart system will be adjustable to household activities with real-time waste monitoring.

Design of Smart Trash Bin

The purpose of this study is to identify the effect of high-tech bins on people’s interest in disposing trash. The method used in this study is a quantitative descriptive method and literature study to analyses community perceptions of smart trash bin. The results of this study state that the mind-set of the community in disposing trash increased after the existence of smart trash bin project. These results were obtained because the community became more interested in disposing trash in the presence of unique designs and diverse functions of these high-tech bins. This study concluded that smart trash bin can increase people’s interest in disposing garbage in its place.

A Persuasive Technology for Managing Waste Disposal through Smart Trash Bin and Waste Disposal Tracker

<p>Waste management issue is a relevant topic that had been focused on many persuasive technologies. This issue is not only related to getting disposed of waste in proper places but also reducing waste disposal volume. This paper proposes a persuasive system that aims both goals by providing a smart trash bin and waste disposal tracker. The smart trash bin is an IoT-featured trash bin whereas waste disposal tracker is a mobile application which can record user daily waste disposal volume statistic. Based on the evaluation, our proposed system has achieved both goals. Additionally, it also solves several impediments such as incapability of moral background to encourage people to dispose waste on the trash bin, boring and monotonous waste disposal activity, and discouragement for disposing waste due to full trash bin. In order to attract people, our system includes attractive mechanisms such as playful experience, reflective experience, and gamification. Playful experience is applied to a smart trash bin, whereas the other two are applied to the waste disposal tracker.</p>

Design of IoT based Garbage Segregation for Automatic Smart Trash Bin using NI LabVIEW

A Smart Trash Bin segregates wastes by itself as degradable wastes and non-degradable wastes with the help of sensors and motors, interfaced with NI myRIO. Rapid changes in technology, low initial cost and planned obsolescence have resulted in a fast-growing surplus of wastes all around the globe. People dump wastes on roadsides, which is not picked up regularly by the people responsible. It s proposed to separate the wastes into categories like degradable and non-degradable will take place in an effectively closed manner .The entire process of waste input, level and segregation is monitored and controlled by the reconfigurable IO using sensors , thereby reducing the open decomposition of organic wastes, thus curbing the growth of micro organisms.

The implementation of smart trash as smart environment concept

One of the efforts to improve the quality of urban environment is smart environment concept that has become one of six of smart city indicators such as smart government, smart economy, smart people, smart mobility, and smart living. Smart environment means an environment that provides comfort, resources, physical and nonphysical beauty, and visual for the people, also students in their schools. This research aimed to apply the concept of smart trash bin in schools. This smart trash bin that detects rubbish based on rubbish group (plastic and metal). In addition, the smart trash bin has a function as education for the students as well. It has explanation about knowledge and how to use the trash bin so the students have awareness to keep environment clean and beauty. The research used Research and Development method from Borg and Gall model. The target of this research was the students in elementary school. The final result of this smart trash bin was a feasibility test product. There will be a test for the students using questionnaire. So that this smart trash bin is effective to improve the knowledge of students about rubbish.

The Design and Implementation of Smart Trash Bin

This paper presents a cost-effective design of an intelligent waste container for small-scale cases. This system is based on Arduino Nano board and an ultrasonic sensor to monitor the fullness level of the container and give SMS alerts using a GSM module. The system is powered by lithium battery power bank supported by solar cell panel. The system provides an option of charging external portable devices using the power bank. Moreover, the system will store usage events, recorded by PIR sensor, and fullness events on a memory card, which is also used to play audio message using a speaker, when the bin is being used. Finally, the system is implemented successfully with an acceptable overall cost for the intended application. The system performance was found satisfactory according to the obtained test results.

Improved mode of preventing the rapid destruction of gas retorts: Patent granted to Alfred Monnier, Camden, New Jersey, February 26, 1857

Municipal solid waste (MSW) is an increasing waste resource and challenging task to solve environmental pollution and waste collection problems. The smart trash bin is sufficient equipment to reduce human intervention and improve living conditions, lacking multifunctional purposes. To solve the problem that traditional trash can lacks self-identification of recyclable garbage and nonrecyclable garbage, a smart trash bin based on WiFi environment and Arduino control is proposed. The smart trash bin takes Arduino as its master controller and interacts with Arduino in the WiFi environment to realize automatic garbage classification and communication between people and trash bin. This paper aims to describe the hardware and software design ideas of trash bins in the implementation process, and the mechanism of garbage classification and the application of the Internet of things in garbage recycling are emphatically studied. The results indicate that the system can run stably and achieve accurate classification within 2 seconds, which reduces the waste of resources, changes the traditional garbage management mode, improves management efficiency, and realizes recycling of garbage.