Reverse Vending Machine Using TCRT5000 and Inductive Proximity Sensors for Bottles and Cans Sorting

The problem of plastic waste is being addressed in a variety of ways, ranging from manual waste sorting to reverse vending machines. On the other side, businesses are becoming increasingly concerned about waste management. Several ways to producing reverse vending machines have been tested, including the use of plastic sensors. However, the findings were unsatisfactory due to imprecise detection. This study looks into the use of ESP32-Cam combined with machine learning for high-precision plastic bottle detection in reverse vending machines. It is envisioned that high-precision plastic bottle detection would be used in reverse vending machines. It is intended that by providing an incentive for each identified plastic bottle, people will be motivated to collect plastic bottles and deposit them into reverse vending machines, thereby supporting digital humanities through enhanced waste management practices.

To protect our planet, the material recycling of domestic waste is necessary. Since the COVID-19 pandemic began, the volume of domestic waste has surged overwhelmingly, and many countries suffered from poor waste management. Increased demand for food delivery and online shopping led to a huge surge in plastic and paper waste which came from natural resources. To reduce the consumption of resources and protect the environment from pollution, such as that from landfills, waste should be recycled. One of precious recyclable materials from household waste is liquid cartons that are made of high-quality paper. To promote sustainable recycling, this paper proposes a vision-based inspection module based on convolutional neural networks via transfer learning (CNN-TL) for collecting liquid packaging cartons in the reverse vending machine (RVM). The RVM is an unmanned automatic waste collector, and thus it needs the intelligence to inspect whether a deposited item is acceptable or not. The whole processing algorithm for collecting cartons, including the inspection step, is presented. When the waste is inserted into the RVM by a user after scanning the barcode on the waste, it is relocated to the inspection module, and the item is weighed. To develop the inspector, an experimental set-up with a video camera was built for image data generation and preparation. Using the image data, the inspection agent was trained. To make a good selection for the model, 17 pretrained CNN models were evaluated, and DenseNet121 was selected. To access the performance of the cameras, four different types were also evaluated. With the same CNN model, this paper found the effect of the number of training epochs being set to 10, 100, and 500. In the results, the most accurate agent was the 500-epoch model, as expected. By using the RVM process logic with this model, the results showed that the accuracy of detection was over 99% (overall probability from three inspections), and the time to inspect one item was less than 2 s. In conclusion, the proposed model was verified for whether it would be applicable to the RVM, as it could distinguish liquid cartons from other types of paper waste.

With the ever-increasing amount of waste disposal by mankind, the requirement for waste management is paramount. Apart from dumping waste in landfills, recycling is another popular solution adopted by the world to manage waste. As an effective collection mechanism of plastic waste, automatic recycle bins are employed in many countries in common places like subways and, malls. Furthermore, different rewarding mechanisms are in place to motivate the consumers to return the plastic waste. Reverse vending machines which encourage the collection of plastic waste and provide rewards are used in some countries. However, existing reverse vending machines lack features like separating plastic based on their plastic category. PET bottles and Yoghurt cups are some of the mostly disposed plastic containers in Sri Lanka. There are companies that use these types only to recycle and manufacture unique recycled products. This paper focuses on developing a reverse vending machine with plastic type sorting function to be used in the Sri Lankan context. The existing mechanisms were reviewed and a solution is designed to operate with Near-infrared (MR) plastic sorting and gravity transfer method. Furthermore, an appropriate rewarding mechanism is also proposed.

In this paper, an inductive proximity sensor with a longer range when compared to its diameter is presented. This sensor is intended to guide doctors, while performing surgery to remove metal shrapnel from victims of bomb blasts, gun fire, land mines etc. Presently doctors rely on imaging systems to locate shrapnel in the victim's body before surgery. Effectiveness of surgery and recovery solely depends on the doctors' skill to trace the shrapnel. In some cases the shrapnel may be visible in the images, but it may be untraceable during surgery. So in such cases, an inductive proximity sensor which is small enough to be introduced into the victim's body and can direct the recovery tool effectively to the exact location of the shrapnel, during the surgery, will be very useful to the doctor. Such a sensor, along with its details and experimental results are presented in this paper. This sensor works on a new comparison based method to detect tiny targets, as the detector size is a constraint here. The sensor can detect shrapnel materials such as steel, brass and Aluminium. A smaller, modified version of this sensor is also presented in the paper, along with a study of the effect of body tissues on sensor performance.

Collection of plastic bottles by reverse vending machine using object detection technique

To enhance awareness of environmental cleanliness and prevent the spread of diseases or viruses, it is sometimes necessary to employ unique methods to attract people's interest, thereby encouraging them to dispose of waste properly. Traditional trash bins generally require manual operation to open and close, which can be inconvenient for users and increase interaction between people and the trash bin. Moreover, manual trash bins often struggle to manage waste when they are full. This research, conducted by Institut Teknologi Nasional, offers a solution by designing a smart trash bin based on Arduino Uno, utilizing the HC-SR04 or ultrasonic sensors, a servo motor, and a buzzer or speaker. In this smart trash bin, the HC-SR04 ultrasonic sensor is used to detect distance, while the servo motor functions to open and close the lid. The buzzer or speaker provides notifications when the lid is about to open or when the trash bin is full.

Smart Waste Management (SWM) system is a waste management system that tracks the status of fill level of trash bins equipped with ultrasonic sensors and tracks GPS-equipped trash collection trucks. The problems identified are the overflowing trash bins especially in public areas with high population density and the complaints from the residents or public complaints regarding the punctuality of trash collection trucks. The objectives of the project are to design a Smart Waste Management (SWM) system based on Bootstrap platform, develop the system and test its functionality in fulfilling the requirements of the project. The methodological approach selected in this project is the waterfall methodology in which it comprises of four crucial phases: planning and analysis, system design, system implementation and system testing whereby each phase must be completed systematically prior to the commencement of subsequent phase. It is expected that the Smart Waste Management (SWM) system would be able to fulfill all of the project's objectives. This system is aimed to address the problems of overflowing trash bins and public complaints on trash collection trucks. The development of this system brings a huge significance in which operators would be able to know which trash bins require immediate collection and request for immediate dispatch by collection trucks. This method is seen to be more efficient compared to routine collection. Operators would also be able to track the relevant dispatch trucks through this convenient system.

Nowadays, inductive proximity sensor and mobile robot are one of the most interesting topics attracting scientists. With enhancement techniques from using sensor for controlling mobile robots which can be developed more in the future. Additionally, measuring of static performance of inductive proximity sensor is also essential because the testing and navigation systems perform more exactly by result information from the experiment by assaying the output signal. In this paper, the hand-made measurement system is used to verify again the static performance of proximity sensor with ferrous, non-ferrous and alloy metal tape. Simultaneously, improve static properties of typical tape metal through the relationship between the output signal and the sensing distance of sensor. According to theoretical basis, the relationship of the static parameters can be determined such as: thickness of metal, sensing distance, dimension of metal, and so on. The testing results have shown the output signal of proximity sensor in the model and theory is not similar. The final data will accommodate some information about the relationship of the thickness of metal tape and the sensing distance of proximity sensor, the different affects of position sensor and optimum operation range of mobile robot.

At present, there are many types of beverage packages such as cans and plastic bottles which lead to a large number of waste beverage cans. Furthermore, throwing beverage cans away without management tends to be an ineffective way to get optimal utilization of resources. Hence, the primary emphasis of this work is on the development of automatic sorting of beverage cans for reverse vending machines. In addition, the accuracy testing of sorting beverage cans by the machine was designed based on three techniques which are easy to implement and which will bring sustainable energy innovations with communities’ participation. There are two sampling groups of cans and plastic bottles in the experimental studies. The first group is the group which already has data in the system for using this in a prototype of sorting process. The latter one is the group without data in the system or which has never been used before.
 Furthermore, the reverse vending machine has two types of proximity sensors; inductive and capacitive which work together. The experimental results of sorting beverage cans and bottles on two sample groups show that the average accuracy of sorting is 99.20%. The sorting of beverage cans and bottles based on magnetic hinge and barcode provides an average accuracy of 79.20% and 50.00%, respectively. Classifying using the proximity sensor has the fastest operation with an average of 2.66 seconds, followed by barcode and hinge. Those takes 4.01 and 5.21 seconds, respectively.

A novel inductive proximity sensor system is accomplished in this paper. Primarily this system uses a modulated magnetic field generator (modulation of current in a coil) and a lock-in receiver which demodulates the magnetic flux density by using a Hall effect device. In contrast to published sensors this approach increases the signal-to-noise ratio (SNR) by a demodulation and a subsequent integration process which is implemented in the lock-in receiver at an isochronous suppression of DC or AC modulated background magnetic flux density. The performance is predicted by simulation and validated by a demonstrator. It is shown that the demodulation inductive proximity sensor works in a hostile environment in which the amplitude of a background magnetic flux density has a similar (or higher) amplitude compared to the active modulated flux density.

The government of India aims at “Swachh Bharat Mission” and for that we need smart city with smart streets enabled with smart garbage monitoring system. We see garbage bins around us placed at public places overflowing with due to increase in waste and results into unhygienic conditions for people and leads to deadly diseases. Thus to improve this situation, we proposed this project. In our proposed system, there are multiple smart garbage trash bins on a microcontroller board platform (Arduino Board) located throughout any city or the campus or hospital. The Arduino Board is interfaced with GSM modem and ultrasonic sensor. Once the level of threshold is being crossed, then ultrasonic sensors will trigger the GSM module which in turn continuously alert the authorised person by sending SMS reminder after until the dustbin is cleaned. Beside this, we will also create the central system that will keep showing us the current status of garbage on mobile web browser with html page by wi-fi. With the help of this, we will create shortest path for garbage collection vehicles using Dijkstra Algorithm. This is real time waste management by using smart trash bins that can be accessed anytime anywhere by the concerned person. Keywords: IoT; Smart city; Smart Garbage Bins; Arduino; Ultrasonic Sensors; GSM; Real time Analytics; Route Optimization

The prevalence of polyethylene terephthalate (PET) in beverage packaging has increased microplastic (MP) accumulation in the environment. MP can become a component of air pollution, especifically of particulate matter with a diameter of less than 2.5 microns (PM2.5). Unfortunately, Thailand has a low recycling rate for plastic bottles, with only 4.5% being recycled. Reverse Vending Machines (RVMs) were introduced in the early 2010s as a potential solution to this problem. RVMs incentivize recycling by providing rewards or refunds for each bottle deposited, thereby reducing the amount of PET waste and MP in the environment. This study analyzed usage and waste collection data from RVMs located at 15 locations of a hypermarket chain in Thailand from June 2020 to December 2022. The results showed that the average PET bottles collected from each machine was approximately 670 kg per year, which was lower than the break-even point of 3,200 kg per year. Economic feasibility indicators also suggested that the use of RVMs might not be economically sound. This study proposed suggestions to improve the business model of RVMs and offered policy recommendations to the government on how to enhance the effectiveness of RVMs.

Improper waste disposal remains to be one of the most salient global environmental concerns. Consequential to economic growth and consumerism, the praxis of sustainability has become stunted as the amount of waste illicitly discarded continue to swell over the years, harming ecosystems, exacerbating global warming and aggravates human adversity. As such, the primary contributors for this concern are Polyethylene terephthalate (PET) bottles and cans, which are widely accessible and also extensively utilized for daily consumption. However, while many countries already have efficient waste management mechanisms in place, challenges regarding recycling efforts persist in afflicting developing countries including the Philippines. Considering this persistent and wide-scale issue, 'Bote-Cannected' is a reverse vending machine that was designed and built to encourage recycling by accepting both plastic bottles and cans for disposal. Delving on the design, Bote-Cannected's system utilized Arduino and Raspberry Pi technologies to automate the sorting and processing of items. Thereafter, the said machine was made to automatically segregate items one at a time, and assign points based on material type and size. Despite minor challenges linked to the design, durability, and overall functionality, 'Bote-Cannected' received high satisfaction ratings from users. Ultimately, its successful application showcased its strong potential in encouraging recycling behaviours and address pressing environmental concerns.

Within this recent years, the maker movement has been developed widely and rapidly in many countries. It encourages individuals to become a maker who is capable of developing a product or design by a low cost process and cheap facilities. Unlike current manufacturers, the makers' products are usually built by a small batch production. It exactly fits the needs and requirements for the age of mass customization. In order to speed up the development of the maker movement, low cost facilities are needed. About the need, makers and engineers have started to develop a set of open sources to freely provide people to build their own machines. 3D printers like Prusa i3 and Rostock are the topical examples. Those cheap machines become makers' major equipment to build their products. Of course, a 3D printer associated with multiple functions definitely can satisfy more makers' building tasks. Based on this fact, this paper is proposed to develop an integrated system which contains both functions of 3D printing and Laser carving in one machine. As we knew, 3D printing is an additive manufacturing technology and Laser carving is a subtractive manufacturing technology. They utilize completely opposite approaches to build their parts, but they are controlled digitally. In the machine, the 3D printing is based on the technology of the Fused Deposition Modeling. It extrudes plastic filament from a nozzle and deposits melted plastic along planned paths layer by layer until a part is completed. For a high quality of printing, the height of the nozzle for printing the first layer is an important control parameter. If the height is too high, it may cause the printed part to fail to stick on the print bed. If the height is too low, it may stop melted plastic out from the nozzle. In order to smooth the printing task, an inductive proximity sensor was installed to develop an auto-bed-leveling system to optimally locate the height of the printer nozzle during a print job. For Laser carving, the auto-bed-leveling system can be used to locate the Laser at optimal height to execute its carving task. This paper presents a designed platform on which an extruder of 3D print head and Laser can be installed without problem. For making auto-bed-leveling work perfectly with Laser carving, an investigation of the Laser carvings at different heights are presented. In addition, a calibration to obtain optimal height is also presented in the paper. This paper presented a detail of developing an integration of 3D printer and Laser carving. It is useful to makers to own a multifunction of machine for their product development.

Shrapnel injury is a major cause of death in victims of bomb blast, land mines and gun fire. In this paper, a Giant Magneto Resistance (GMR) sensor based online surgical tool that helps to remove metal shrapnel from victim's body is presented. This tool is intended to guide the surgeon to the exact location of the shrapnel during surgery. Presently doctors rely on imaging systems to locate them before surgery. Effectiveness of surgery solely depends on the doctors' skill to trace them, as these images do not provide real-time information of the location of the shrapnel during surgery. Therefore, in some cases, the shrapnel, in spite of being visible in the images, may become untraceable during surgery. So in such cases, a sensing tool that can guide the doctor to the location of the shrapnel will be very effective. An inductive proximity sensor can serve this purpose, but its output can be affected by its lead inductance or other parasitic circuit parameters. Therefore in order to overcome such effects, a GMR based sensing tool is proposed here. The details and experimental results obtained from this tool are presented in this paper. The tool can detect both ferromagnetic and paramagnetic metal targets.