Application of Capacitance Proximity Sensor for the Identification of Paper and Plastic from Recycling Materials

Ahmad, Irfana Kabir; Mukhlisin, Muhammad; Basri, Hassan

doi:10.19026/rjaset.12.2880

Cited by 16 publications

(5 citation statements)

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“…A metal detector [15] detects metal waste via the principle of electrical induction, whilst glass collected from recycling bins typically is heavier than other types of waste; hence, a weight sensor [16] is utilised to segregate glass waste. Some researchers have also utilised capacitive proximity sensors [17], [18] to identify papers and plastics, as the amount of light passing through each material is different due to their distinct materials and properties. However, using optical sensor may be inaccurate and inefficient as both plastic and paper waste types can have different properties from their normal properties; some plastic can be opaque, and some papers can be thick, which make the determination of waste types using optical sensors to be inaccurate.…”

Section: Related Work 21 Automatic Waste Segregation Technologiesmentioning

confidence: 99%

The Development of an Automated Waste Segregator

Azis,

Suhaimi,

Abas

2023

IJIE

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Accumulation of waste isa major global concern,and recycling is considered one of the most effective methods to solve the problem. However, recycling requiresproper segregation of wasteaccording to waste types.This paper developsan automatic waste segregator, capable of identifying andsegregatingsix types of wastes; metal, paper, plastic, glass, cardboard, and others. The proposed systememploys Convolutional Neural Network (CNN) technology, specifically the Inception-v3 architecture, as well as two physical sensors;weight and metal sensors, to classify and segregate the waste. Overall classification accuracy of the system is 86.7%.Classificationperformance of the developed waste segregatorhas been evaluated further using the precision and recall; with high precision obtained for cardboard, metal, and other waste types, and high recall for metal and glass. Theseresults demonstrate the applicability of the developed system in effectively segregating waste at source, and thereby, reducing the need for the commonly labor-intensive segregation at waste facility. Deploying the system has the potential of reducing waste management problems by assisting recycling companies in sorting recyclablewaste, throughautomation.

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Section: Related Work 21 Automatic Waste Segregation Technologiesmentioning

confidence: 99%

The Development of an Automated Waste Segregator

Azis,

Suhaimi,

Abas

2023

IJIE

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“…The main sensors currently applied in smart waste systems can provide information about the waste volume of a container. These transducers may be capacitive [ 20 ], ultrasonic [ 21 ], infrared, Time of Flight (ToF) [ 22 ], or Guided wave radar (GWR). Each one of these transducers has different features that must be considered, such as range, measuring accuracy and amplitude of the working angle (described in Table 1 ).…”

Section: State Of the Artmentioning

confidence: 99%

Smart Waste Collection System with Low Consumption LoRaWAN Nodes and Route Optimization

Lozano

Caridad

Paz

et al. 2018

Sensors

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New solutions for managing waste have emerged due to the rise of Smart Cities and the Internet of Things. These solutions can also be applied in rural environments, but they require the deployment of a low cost and low consumption sensor network which can be used by different applications. Wireless technologies such as LoRa and low consumption microcontrollers, such as the SAM L21 family make the implementation and deployment of this kind of sensor network possible. This paper introduces a waste monitoring and management platform used in rural environments. A prototype of a low consumption wireless node is developed to obtain measurements of the weight, filling volume and temperature of a waste container. This monitoring allows the progressive filling data of every town container to be gathered and analysed as well as creating alerts in case of incidence. The platform features a module for optimising waste collection routes. This module dynamically generates routes from data obtained through the deployed nodes to save energy, time and consequently, costs. It also features a mobile application for the collection fleet which guides every driver through the best route—previously calculated for each journey. This paper presents a case study performed in the region of Salamanca to evaluate the efficiency and the viability of the system’s implementation. Data used for this case study come from open data sources, the report of the Castilla y León waste management plan and data from public tender procedures in the region of Salamanca. The results of the case study show a developed node with a great lifetime of operation, a large coverage with small deployment of antennas in the region, and a route optimization system which uses weight and volume measured by the node, and provides savings in cost, time and workforce compared to a static collection route approach.

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“…Besides, capacitive proximity sensors have also been used to identify different materials based on their distinct dielectric constants. In Ahmad et al (2016), a capacitive proximity sensor is designed to automatically identify paper and plastic from recycling materials without manual operation. In Ding et al (2018), a noncontact material detection method using a capacitive proximity sensor is proposed.…”

Section: Introductionmentioning

confidence: 99%

A new planar capacitive sensor with high sensitivity for proximity sensing of an approaching conductor

Wang,

Li,

Shi

et al. 2024

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Purpose With the development of artificial intelligence, proximity sensors show their great potential in intelligent perception. This paper aims to propose a new planar capacitive sensor for the proximity sensing of a conductor. Design/methodology/approach Different from traditional structures, the proposed sensor is characterized by sawtooth-structured electrodes. A series of numerical simulations have been carried out to study the impact of different geometrical parameters such as the width of the main trunk, the width of the sawtooth and the number of sawtooths. In addition, the impact of the lateral offset of the approaching graphite block is investigated. Findings It is found that sensitivity is improved with the increase of the main trunk with, sawtooth width and sawtooth number while a larger lateral offset leads to a decrease in sensitivity. The performance of the proposed planar capacitive proximity sensor is also compared with two conventional planar capacitive sensors. The results show that the proposed planar capacitive sensor is obviously more sensitive than the two conventional planar capacitive sensors. Originality/value In this paper, a new planar capacitive sensor is proposed for the proximity sensing of a conductor. The results show that the capacitive sensor with the novel structure is obviously more sensitive than the traditional structures in the detection of the proximity conductor.

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Application of Capacitance Proximity Sensor for the Identification of Paper and Plastic from Recycling Materials

Cited by 16 publications

References 0 publications

The Development of an Automated Waste Segregator

The Development of an Automated Waste Segregator

Smart Waste Collection System with Low Consumption LoRaWAN Nodes and Route Optimization

A new planar capacitive sensor with high sensitivity for proximity sensing of an approaching conductor

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