Browsing by Author "Rajapaksha, S"

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Embargo
Adding Common Sense to Robots by Completing the Incomplete Natural Language Instructions
(IEEE, 2022-07-18) De Silva, G. W. M. H. P.; Rajapaksha, S; Jayawardena, C
This system is developed to identify and complete the human’s instructions or incomplete sentences given by a user as a command. It would facilitate the interaction between the human and mobile service robots. However, when humans give the instruction, there can be incompleteness or else missing the information related to the environment. That is because humans, generally based on common sense, depending on the environment. Then the human brain can complete all those incomplete sentences by using common sense knowledge. This paper itself introduced a model of a service robot who can compete with the given incomplete instructions, display the related sentences or words, and finally move to the related objects in the environment. First, it will consider and identify the objects in the environment and then consider the given natural language instruction by humans. As a first step of the approach, complete the incomplete sentences. Those sentences are coming as natural language instructions. By parsing it into as the frame can identify the related words by using the created model or can call as language model and here used some identify words from the human common sense also, then the service robot will learn about the commonsense knowledge automatically from the parsing sentences as a speaker. Considering all the parsing sentences, it calculates and measures the accuracy of this service robot model. Simply this is a commonsense reasoning model. The result of the provided solution can enable the robot model that works in a ROS environment to identify and automatically perform the tasks.
Embargo
Autonomous Hydroponic Environment with Live Remote Consulting System for Strawberry Farming
(IEEE, 2022-12-09) Samaranayake, S.L; Krishmal, S; Cooray, P.L.R.K; Senatilaka, T; Rajapaksha, S; Nuwanthika, W.S
Strawberries are a very popular fruit and are widely consumed all over the world. Due to its nutritional value, its consumption has increased tremendously in recent times. Strawberry, which has such high health and economic value, is grown in only one area in Sri Lanka. This is since the climate in those areas is favorable for strawberries. Using the Internet of Things, image processing, and machine learning, this research proposed a design for a closed environment with automatic monitoring and controlling of environmental factors and nutrition required for strawberry cultivation with the capability of remote live monitoring and analysis of each plant. Also, the proposed system captures the images of each strawberry plant using a camera navigation system and analyses those images using a machine learning algorithm to identify the growing stage. This decision making process was verified using strawberry pictures acquired from a strawberry farm. In addition, current capturing images can use in the next growth cycle to increase accuracy. The proposed system can be easily expanded by increasing the height of the tower and refrigeration power. Through this, strawberry cultivation can be expanded to all parts of Sri Lanka by overcoming climatic and geographical limitations.
Embargo
Behavior & Bio metric based Masquerade Detection Mobile Application
(Springer, Cham, 2019-07-29) Chandrasekara, P; Abeywardana, H; Rajapaksha, S; Sanjeevan, p
Mobile phone has become an important asset when it comes to information security since it has become a virtual safe. However, to protect the information inside the mobile, the manufacturers use the technologies as password protection, face recognition or fingerprint protection. Nevertheless, it is clear that these security methods can be bypassed. That is when the urge of a post-authentication is coming to the surface. In order to protect the phone from an unauthorized or illegitimate user this method is proposed as a solution. The aim of the proposed solution is to detect the illegitimate user by monitoring the behavior of the user by four main parameters. They are: 1) Keystroke dynamics with a customized keyboard; 2) location detection; 3) voice recognition; 4) Application usage. In the initial state machine learning is used to train this mobile application with the authentic user’s behavior and they are stored in a central database. After the initial training period the application is monitoring the usage and comparing it with the already saved data of the user. Another unique feature of this is the prevention mechanism it executes when an illegitimate user is detected. Furthermore, this application is proposed as an inbuilt application in order to avoid the deletion of app or uninstallation of the app by the intruder. With this Application which is introduced as “AuthDNA” will help you to protect the sensitive information of your mobile device in a case of theft and bypassing of initial authentication.
Embargo
Cloud-based Salesman-Bot for Ontology-based Negotiation
(IEEE, 2023-04-06) Fernando, A; Rahubedda, T; Jayasinghe, B; Mallikahewa, S; Hettiarachchi, O; Rajapaksha, S
We have proposed a cloud-based ChatBot (Salesman-Bot) approach to handling multiple negotiation scenarios in a supermarket environment. The web application is a simple interface that can be implemented on a single standalone device or interacted with through a mobile phone. The Salesman-Bot responds both via text and speech. By introducing a Salesman-Bot, efficient negotiation, with quick preferences and suggestions can be provided. A new architecture proposed to operate the Salesman-Bot together with Google APIs and libraries such as Natural Language AI, Vision AI, Speech to Text API, Text to Speech API and Machine Learning using TensorFlow. The application also uses the Google Cloud Platform with related services such as Google App Engine. The goal is to make ChatBots more efficient in negotiating in different business scenarios. This paper presents the work carried out with ontology and machine learning in a cloud-based environment to handle multiple negotiation scenarios based on a negotiation hierarchy. It also proposes the opportunities and drawbacks of such a system.
Embargo
Computer Vision Based Navigation Robot
(IEEE, 2022-12-26) Haputhanthri, M; Himasha, C; Balasooriya, H; Herath, M; Rajapaksha, S; Harshanath, S.M.B.
The majority of industrial environments and homewares need help when exploring unknown locations owing to a lack of understanding about the building structure and the various impediments that may be faced while transporting products from one spot to another. This is because there is a lack of knowledge about the building structure and the potential obstacles that may be encountered. This paper provides “Computer Vision-Based Navigation Robot” as a strategy for indoor navigation with optimal accessibility, usability, and security, decreasing issues that the user may encounter when traveling through indoor and outdoor areas with real-time monitoring of the most up to date IoT technology. The article is titled “Indoor Navigation with Optimal Accessibility, Usability, and Security.” This article proposes “Computer Vision-Based Navigation Robot” as a solution for interior navigation that provides optimum accessibility, usability, and security. This is done in order to tackle the issue that was presented before. Since the readers of this post include people who work in industry as well as physically challenged people who live alone, CVBN Robot takes object-based inputs from its surroundings. This is because the audience for this essay includes both groups of people. This study also covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot. This connection enables real-time position and status updates for the robot as it navigates a known but unknown interior environment. In addition, this study covers a variety of methods for localization, sensors for the detection of obstacles, and a protocol for an Internet of Things connection between the server and the robot.
Embargo
Development of Agent-Based Centralized Tool For Analyzing and Managing Security-Enhanced Linux Policies using WebSocket Protocol
(IEEE, 2022-04-14) Kularatna, I. M; Rajapaksha, S
The SELinux facilitates and includes an extensible "MAC" structure built within the Linux kernel. An application or a process life cycle that runs as a user has the specific authority to access objects such as files, sockets, and other processes with Linux’s default Discretionary Access Control (DAC). SELinux prescribes the access and the progress privileges of each user, application, process, and the files on the system and administers the communications of these elements utilizing a security strategy that determines how severe or indulgent a given Red Hat Enterprise Linux establishment ought to be. However, its constraints such as, not being user-friendly, having too complicated policies, and complex policy description language, are limiting the implementation of SELinux policies in the Information Technology industry. As a result, there is only a little research available on User Interface-based policy management tools. Even those researches have limitations such as the inability to remotely manage a host/server, manual documentation, and the inability to monitor the systems automatically from a dashboard. In order to overcome said research gap and problems, this research will implement a system using a web-socket technology that facilitates the ability to converse in full-duplex through just one TCP connection. This system is included with a web socket-agent, which can be installed in server endpoints and can change SELinux policies, a web-socket server: which can do live communication with the agent to perform policy changes along with the UI component: to manage policies using the user interface and a database component to store policy details.
Embargo
Development of Agent-Based Centralized Tool For Analyzing and Managing Security-Enhanced Linux Policies using WebSocket Protocol
(IEEE, 2022-02-23) Rajapaksha, S; Kularatna, I. M
The SELinux facilitates and includes an extensible "MAC" structure built within the Linux kernel. An application or a process life cycle that runs as a user has the specific authority to access objects such as files, sockets, and other processes with Linux’s default Discretionary Access Control (DAC). SELinux prescribes the access and the progress privileges of each user, application, process, and the files on the system and administers the communications of these elements utilizing a security strategy that determines how severe or indulgent a given Red Hat Enterprise Linux establishment ought to be. However, its constraints such as, not being user-friendly, having too complicated policies, and complex policy description language, are limiting the implementation of SELinux policies in the Information Technology industry. As a result, there is only a little research available on User Interface-based policy management tools. Even those researches have limitations such as the inability to remotely manage a host/server, manual documentation, and the inability to monitor the systems automatically from a dashboard. In order to overcome said research gap and problems, this research will implement a system using a web-socket technology that facilitates the ability to converse in full-duplex through just one TCP connection. This system is included with a web socket-agent, which can be installed in server endpoints and can change SELinux policies, a web-socket server: which can do live communication with the agent to perform policy changes along with the UI component: to manage policies using the user interface and a database component to store policy details.
Embargo
Elderly Care Home Robot using Emotion Recognition, Voice Recognition and Medicine Scheduling
(IEEE, 2022-12-26) Kularatne, B.M.U.S.; Basnayake, B.M.J.N.; Sathmini, P.D.L.A.M.; Sewwandi, G.V.U; Rajapaksha, S; De Silva, D
The robotic concept is used for several tasks to easier human day-to-day tasks. There are various recreational studies have been done on the elderly people’s care system. In this study, the system can identify the elderly people’s emotional status using thermal image processing that eliminates the halo effect issue in thermal images using a single discriminator Cycle-GAN model, serving medicine to elderly people by moving towards the elderly person while avoiding obstacles using point to point algorithm and obstacle avoidance and identify the semantic analysis by using web ontology based language. The integrated system is evaluated using the Gazebo simulator because the cost is lower than implementing the features in a real robot.
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Farming Through Technology Driven Solutions For Agriculture Industry Ceylon E-Agro mobile application-find technology based solutions for agricultural problems
(Institute of Electrical and Electronics Engineers, 2022-09-16) Imalka, L.A.; Gunawardana, K.G.A.; Kodithuwakku, K.M.S.K; Arachchi, H.K.E; Harshanath, S.M.B; Rajapaksha, S
Many developing countries are based on the agricultural sector. More than 60 percent of the population depends on this sector. This project is focused on maize cultivation. In agriculture, farmers play the most important role. Currently, farmers are facing many problems related to maize cultivation in Sri Lanka. This mobile application will help the maize farmers to overcome these difficulties and provide a good consumer demand for maize cultivation. Through this mobile application, the farmer can find solutions for pest & diseases in maize, fire threat in the farm field. AI based Agri Agent will be provide real-time solutions, bring the farmers and the buyers into the one platform, and provide price prophesying, price index feature. IoT based smart farming features will be provided to remain soil moisture and quality of soil for maize plantation.
Open Access
Identification of Some Major Research Gaps in Lean Manufacturing and Industry 4.0 Integration
(SLIIT Business School, 2023-12-14) Rajapaksha, S; Jayarathne, P.G.S.A; Galdolage, S
In the contemporary business world, digitalization has become a significant factor in economic development. Lean is a prominent topic in both academia and business. Due to the evolution of digital technologies that promote Industry 4.0 because of the industrial revolution, the integration of Lean Manufacturing and Industry 4.0 has attracted the attention of academics and managers. This conceptual paper discusses the integration of Lean Manufacturing and Industry 4.0, as well as the research gaps and prospective research opportunities related to integration. Systematic Literature Review (SLR) in the PRISMA framework has been used to identify research gaps, and future studies could be planned to close these gaps to benefit academia and industry stakeholders. Keyword co-occurrence analysis has been performed using VOSviewer software to identify areas that need the attention of researchers. Articles were extracted from the Scopus database using the keywords "Lean Manufacturing" and "Industry 4.0". This study concentrates on identifying research gaps that industry leaders and managers would be interested in, rather than the gaps in conceptual nature.
Open Access
Improved Path Planning for Multi-Robot Systems Using a Hybrid Probabilistic Roadmap and Genetic Algorithm Approach
(Department of Agribusiness, Universitas Muhammadiyah Yogyakarta, 2025-03-24) Jathunga, T; Rajapaksha, S
This study focuses on the development and application of an improved Probabilistic Roadmap (PRM) algorithm enhanced with Genetic Algorithms (GA) for multi-robot path planning in dynamic environments. Traditional PRM-based methods often struggle with optimizing path length and minimizing turns, particularly in complex, multi-agent scenarios. To address these limitations, we propose a hybrid PRM-GA approach that incorporates genetic operators to evolve optimal paths for multiple robots in real-time.The research contribution is an enhanced PRM-GA framework that improves efficiency in multi-robot navigation by integrating evolutionary techniques for dynamic obstacle handling and optimized path generation.The research methodology involves testing the algorithm in various environments, including varying robot numbers and environmental complexities, to evaluate its scalability and effectiveness. Our results demonstrate that the PRM-GA algorithm successfully reduces both path lengths and turn counts compared to standard PRM-based methods, ensuring collision-free and smooth paths. The algorithm showed robust performance across different scenarios, effectively handling dynamic obstacles and multi-agent coordination. However, in highly dynamic environments with rapidly changing obstacles and constraints, the algorithm may occasionally produce paths with turn counts and distances similar to or slightly higher than those of simpler approaches due to the need for frequent re-optimization. Future research can explore incorporating additional factors such as energy consumption and time optimization, alongside distance and turns, to further enhance the algorithm's efficiency in real-world applications. Overall, the PRM-GA approach advances the state of the art by offering a more adaptable and scalable solution for multi-robot path planning, with applications in logistics, industrial automation, and autonomous robotics.
Embargo
An Improved Round Robin Algorithm for an Efficient CPU Scheduling
(IEEE, 2022-02-23) Bandara, A. M. O; Rajapaksha, S
The algorithm policy applied by a CPU, to schedule running processes, has an impact on the efficiency of an operating system (OS). As a result, a superior CPU scheduling algorithm leads to higher OS performance while using limited resources and for shorter periods of time. As a result, several strategies have been suggested and implemented to improve CPU scheduling performance. Any scheduler’s primary responsibility is to assign jobs to the most effective and reliable resource available. It’s also a fact that if jobs and resources aren’t planned properly, the entire operating system’s productivity suffers significantly. The "Round Robin" is deemed an effective and fair approach because of each process is allocated the same amount of time quantum. Nevertheless, the effectiveness of the system is determined by the selected time-quantum. The major goal of this research is to develop the present round-robin algorithm by enhancing the time quantum for candidate processes in real-time in such a way that its impartiality is maintained. There is no loss of property. This paper’s proposed algorithm finds the time left in a process’s last turn, and then Determines whether it is time-based on a certain threshold value, should quantum be expanded or not. An arithmetic simulation has been created to demonstrate that the suggested method is correct. It outperforms the traditional round-robin algorithm. In words of several performing metrics such as average waiting time, context switches and the number of turnaround times, the suggested adjusted version of the round- robin algorithm outperforms the traditional round-robin algorithm, according to the results of the experimental investigation.
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Intelligent System to Verify the Effectiveness of Proposed Teacher Transfers Incorporating Human Factors
(IEEE, 2022-02-23) Karunanayake, V; Wanniarachchi, J. C; Karunanayake, p; Rajapaksha, S
A data center architecture can be determined as the basic structure of a cloud computing data center. However, the expected outcome cannot be obtained even though the tools, technologies, and elements are advanced. It is crucial to select the right architecture as architecture used, which directly affects the operational cost and power consumption of the data center. The SDN, Software Defined Networking, is a novel technology of cloud computing. This SDN is used to separate the control panel and forwarding plane as well, as it enables programmable network components. Therefore, the components of the SDN can easily control and managed. This research aimed to select an SDN-based architecture for a data center. Here, there are two parameters of average throughput and average packet delay on the three existing architectures that are tested using simulation. Then the results are compared with each other. In this research, the accuracy correlations among average packet delay and average throughput are investigated. The Obtained results show that Fat-Tree architecture is the best one among VL2 and hybrid architecture consists with flat tree and VL2 technology in terms of their performances.
Embargo
Intelligent Wheelchair with Emotion Analysis and Voice Recognition
(IEEE, 2022-12-26) Perera, S; Gamage, S; Weerasinghe, C; Jayawardena, C; Pathinayake, K; Rajapaksha, S
Intelligent wheelchairs are becoming more and more prevalent in contemporary life, and the peaceful interaction of humans with wheelchairs is one of the most popular research topics. The development of a voice recognition and emotion recognition based intelligent wheelchair framework is being addressed here for truly impaired/disabled people who are unable to operate the wheelchair by hand. The patient can operate the wheelchair using voice commands, and the wheelchair’s Emotion Analysis module recognizes the patient’s face and records the patient’s emotions before sending the information to a cell phone application. A portion of the intelligent wheelchair is made to gather crucial information given by other units and send out emergency calls or notifications to the caregivers. Face recognition technology uses image processing to identify facial expressions by detecting the patient’s face and facial expressions. This helps the other components collect and send data via Internet of Things technologies. Speech – to –Text and Text – to-Speech Methodology is used in the voice recognition module and it captures the voice command data set and extracts the features of the commands.The model is already built and trained to recognize the commands and to send action request to the relevant unit.The Responsive AI auto starts the timer when the patient moves away from the wheelchair, recognizes time and responses back. This unit auto also sends the alert and calls to the guardian when the user has no response.
Embargo
Moving a Robot In Unknown Areas Without Collision Using Robot Operating System
(IEEE, 2022-02-23) Gayashani, K. K. P; Rajapaksha, S; Jayawardena, C
Nowadays, robots have become a most crucial role. With technology development, we can do so many things using robotic technology. There are lots of projects in which robots move in a known area. This study proposes a mechanism to move a robot in an unknown area. We can use this kind of robot in hazardous environments, and we can use this robot in several ways. The proposed system is based on the Robotic Operation System (ROS) and the simulator Gazebo. The obstacle avoidance part is done using a laser sensor. After that, there should be a direction-changing mechanism in the developing algorithm. That implemented using loops. Because after the robot changes direction, it again needs to check whether another object is there in the navigated location. The proposed algorithm was developed with the autonomous navigation mechanism. Map generation is another functionality of this project. It is done using Simultaneous Localization And Mapping (SLAM). Map visualization was done using the Rviz application. With the robot’s movement, the robot’s current position is calculated using x, y, and z coordinates. Also, this project has included reverse navigation functionality. Reverse navigation is a novel section in this research work. The objective of this study and the outcome is to move the robot without having any crashes. Also, we can use this to evaluate dangerous areas. Experimental results of the direction and velocity changes have been mentioned in the results and discussion section.
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Moving Robots in Unknown Environments Using Potential Field Graphs
(IEEE, 2022-02-23) Panagoda, M; Lokuliyanage, M; Senarath, A; Nethmini Nisansala, N. K. V. M; Rajapakshe, R. W. A. D. U; Rajapaksha, S; Jayawardena, C
The purpose of this research paper is to introduce a new navigation algorithm for Robot Operating System (ROS) based robots which will allow complete autonomous traversal in any given indoor environment. Turtle bot3 burger bot is the sample robot chosen for this project. This will be equipped with a Light Detection and Ranging (LIDAR) scanner with the default settings, ultrasound, Intel Real Sense camera, etc. Environment information gathered via these sensors will be sent into a remote computer for processing since the raspberry pie micro-controller with the turtle bot burger is not enough to carry out a high computation-intensive task. Once the information is received series of tasks will be carried out by the remote personal computer before executing the newly developed navigation algorithm. The data from the LIDAR scanner help to generate a 2-dimensional(2D) potential field graph. Then it will later be used for path planning by navigation algorithm. Furthermore, the Real sense camera is used for object boundary detection to produce more accurate data for the navigation algorithm. Once all the data proceed, data will return to the robot, where the navigation algorithm will start execution in parallel with a recovery behavior algorithm and scan algorithm. The recovery behavior algorithm is responsible for guiding the robot to face away from an obstacle in an event where the predetermined path is obstructed. Furthermore, it is responsible for maintaining accurate data in the cost map. Subsequently, the scanning algorithm will be used to generate maps.
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Platform Independent Browser Forensic Tool for Advanced Analysis of Artifacts and Case Management
(IEEE, 2021-12-09) Dissanayake, D; Rajakaruna, S; Ranasinghe, D; Wijesooriya, A; Jayakody, A; Rajapaksha, S
A web browser is a major attack vector which cyber-criminals utilize to land in an environment. The evidence related to the malicious browsing activities can be found in the host which gives valuable information related to the case. These digital footprints involve history, cookies, bookmarks, saved credentials and downloads etc. This paper presents a sophisticated tool aiding the conventional manual investigation process from evidence collection to the final v e rdict b y a u tomating h u man dependent functions, resulting a fast and unbiased analysis of browser forensic artifacts. This tool states its unique value over the existing tools by working operating systems independently, collecting all browsing evidence including deleted artifacts and encrypted saved credentials, automatically analysing the reputation of the extracted evidence, integrating evidence collected from different web browsers into a single timeline, and correlating the adjacent distrustful events inside and outside the host. Eventually, this tool calculates a browsing reputation scorecard and creates a profile for the host, condensing the findings g a thered t h roughout the investigation. The paper presents another important methodology to predict the future browsing reputation score based on the past browsing patterns. Furthermore, multiple cases management feature and dashboard provide a concise overview of overall findings to the forensic investigator.
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ROS Supported Heterogeneous Multiple Robots Registration and Communication with User Instructions
(IEEE, 2022-02-23) Rajapaksha, S; Jayawardena, S; MacDonald, B. A
Different types of heterogeneous multiple service robots are working in the same environment to help humans in many ways in a smart house. These service robots have different capabilities based on the different control and communication systems. The complexity of the programming of the robots is now reduced by using middleware like Robot Operating System (ROS). However, the communication and control of the heterogeneous service robots using very high-level instruction is still tricky because of differences in ROS topics. If a user has issued a high-level instruction to all multiple heterogeneous robots in the same environment, then all robots must complete the given task without considering the software differences in each robot. This research has developed a web-based interface where users can input high-level instruction to all multiple heterogeneous robots running in the same environment. We have used three levels of instructions. Level 01 moves robot forward for the given speed for some distance without obstacles. Level 02 is to move the robot to a specific location without obstacles. Level 03 is to navigate the robot to a goal with some obstacles in the environment. Initially, all robots need to register their software specifications and hardware specification Format (URDF) in the robot registration engine with the help of the ontology. Then all service robots act according to the instruction given by the interpreter. The proposed system was evaluated using a simulated environment with a gazebo using "Turtlebot" and "Tiago" robots. Time complexity analysis of all algorithms was completed using the Big O notation.
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SMART DIARY: Autonomous System for Daily Diary Creation and Prioritization of Daily Activities for Improved Well-Being Using Neural Networks and Machine Learning
(IEEE, 2022-12-09) Abraar, S.F.M.; Thuduhenage, D.T.; Balasubramaniyam, V.P.; Mohanraj, S.R.; Wimalaratne, G; Rajapaksha, S
In the present world, the IT (Information Technology) industry is so advanced that it has opened many opportunities to communities with numerous roles. Even though the industry is growing day by day and providing more opportunities, it has had serious effects on human well-being. If a person fails to control the demands of work or study, such as tasks with higher complexity, an unmanageable workload, pressure, enduring conflicts within the team, and other physical and emotional demands, it could lead that person to exhaustion, anxiety, and stress. Such factors can affect the health of a person in an extremely negative way. The proposed topic “Smart Diary: Auto generation of diary and Prioritization of Daily Activities for Improved Well-Being” is a solution for people with uncontrolled job demands and busy work schedules. This helps to keep track of day-to-day life activities and review them to make better plans for the future. It also helps the user prioritize their daily tasks and provides suggestions for people who are stressed and showcasing negative emotions based on text analysis.
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A Smart Waste Disposal System: To Encourage Proper Waste Disposal
(IEEE, 2022-12-09) Alwis, D; Munasinghe, P; Rajapaksha, S; Ranawaka, B; Krishara, J; Tissera, W
Waste disposal is one of the most important industries in the world. If not maintained properly it would lead to the destruction of the environment. Improper waste disposal is becoming a critical issue in Sri Lanka and the lack of waste segregation, inadequate waste collection methods, the lack of support for waste management from the public are among the root causes of the problem. As a solution we propose an IoT-based solid waste management system that allows garbage bin monitoring, routing of garbage collector trucks, a prediction model and a point rewarding system. As the end result of this research the following prototypes was built; a prototype model of a smart bin with the capabilities of opening and closing by itself and detecting the waste level of the bin, a prototype mobile application for garbage collectors which delivers analysed data on truck position and ensures timeliness, a prototype mobile application for the public which receives the weight and type of solid waste discarded as an input and calculate reward points to encourage the public in proper waste disposal, a prototype web application which delivers statistical data for detailed reports and a prediction model which predicts the amount of waste to be collected in the coming month using machine learning. This is a low-cost IoT-based solution that uses existing resources to handle the massive amounts of garbage collected each day.