## 2 Literature Survey
[17] propose the creation of an integrated system for managing radioactive waste, incorporating a QR code-based approach with real-time monitoring capabilities. This innovative system offers a streamlined and systematic method for handling small-packaged radioactive waste, covering the entire process from generation to treatment. By doing so, it aims to reduce the volume of radioactive waste and subsequently lower disposal costs.The QR code system can store essential information, including the waste generation year, generator details, container specifications, total radioactivity levels, visual representations of contents, and physical characteristics. This system can seamlessly connect with on-site operations through the radioactive waste cycle history management system, significantly enhancing operational efficiency, minimizing the risk of human error, and bolstering reliability in radioactive waste management. Additionally, this safety-focused radioactive waste management system harnesses cutting-edge ICT technologies to enhance monitoring, tracking, and decision-making processes [18]. [PERSON] et al. [19] proposed a municipal waste management system that utilizes deep learning-based classification and cloud computing to reduce the cost of waste classification, monitoring, and collection. The system subdivides recyclable waste into six categories and uses deep-learning convolution neural networks to achieve high accuracy in garbage classification. The envisioned system incorporates IoT devices equipped with sensors to monitor both the total waste generation and the operational status of waste containers. This data is harnessed by the waste management center for real-time decision-making, encompassing adjustments to equipment deployment, maintenance schedules, waste collection, and optimizing vehicle routing plans. MobileNetV3 has been singled out as the optimal and precise classifier for this particular system. [PERSON] et al. [20] examined various technological strategies for solid waste management within smart city contexts. The literature is classified into three key categories: RFID, WSN, and IoT-based methodologies, with IoT-based systems emerging as the most effective among them. In the realm of automating solid waste management in urban environments, LoRaWAN stands out as the preferred communication protocol. The research also pinpoints several areas where further investigation is warranted, including the design of ultra-low-power nodes, the optimization of energy harvesting techniques for self-sustaining nodes, bin-based waste segregation, and the utilization of hybrid network architectures. The paper [21] proposes a smart waste management system called the internet of garbage bins (IoGBs), which uses IoT technology to monitor waste bin fill levels and optimize waste collection schedules, reducing operational costs and improving the sustainability of waste management. Smart cities are being introduced globally, with examples in cities like Mangaluru [22; 23], Seoul [24], Greater Noida [25], and Kerala [26] where innovative QR code-based systems have been successfully implemented for household waste collection. In this system, primary waste collection vehicles, responsible for collecting refuse from door to door, employ QR code scanning technology placed at household entrances during the collection process. Subsequently, the gathered refuse is transferred to secondary collection vehicles, which then transport it to designated disposal sites. Furthermore, beyond waste management, the QR codes installed at residences can serve as versatile tools, facilitating various public services, including the payment of utility bills, property taxes, and telephone bills, among others. [PERSON] et al. [27] have presented a case study conducted in a specific locality to evaluate the efficiency of different household waste collection methods and statistics about the community involved in the waste collection.