# Sensor-Based Solid Waste Handling Systems: A Survey
## 5 IoT-Enabled Solid Waste Management Systems
### Network Architecture
Due to its lightweight nature, the pre-trained object identification model SSDMobilnetV2 can operate well with Raspberry Pi 3 Model B+. The model could detect and classify waste into different categories such as paper, plastic, and metal. Nevertheless, the accuracy of the model can be enhanced by increasing the frequency of training data, the \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Communication** & **Wireless** & **Power** & **Operating** & **Data** & **Modulation** \\
**Technology** & **Range** & **Consumption** & **Frequency** & **Rate** & **Technique** \\ \hline LoRaWAN & \textless{}15 km & Low & Sub-GHz & 0.3–50 kbps & SS Chirp \\ SigFox & 50 km & Low & Sub-GHz & 100 bps & DBPSK \\ NB-IoT & \textless{}35 km & Low & Cellular Bands & 200 kbps & QPSK \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of popular low-power wide-area network. frequency of captured images of waste, and the training period. The work in [52] discusses the suitability of waterproof ultrasonic sensors for measuring the level of waste within a trash bin. The proposed sensing node has been evaluated in the laboratory, demonstrating its efficacy. The value of the waste level inside the bin is determined with a precision of 2-3 cm; this value is sufficient since waste is not spread uniformly inside the bin. Following this initial testing, a network comprising five sensor nodes coupled to a single-channel LoRa gateway is constructed and implemented in real-time. The implementation of an Internet of Things (IoT) architecture for waste management optimization in the context of Smart Cities is presented in [53]. This work describes a novel sensor node topology based on the utilization of low-cost and low-power components. All the sensor nodes are equipped with a single-chip microprocessor, an ultrasound-based sensor for measuring the fill level of trash bins, and a LoRa transmission module. A LoRaWAN network is established to evaluate the performance of the proposed system. Moreover, it evaluates the end node in detail by focusing on energy-saving technologies and strategies, intending to increase battery life by reducing power consumption via hardware and software optimization. A waste monitoring and management system for rural areas is presented in [54]. A low-power wireless node prototype is built to determine the weight, filling level, and temperature of the trash bin. This form of monitoring enables the collection and analysis of progressive filling data for each trash bin, as well as the generation of notifications in the event of an incident. The system enables a module for determining the most efficient waste collection routes. This module constructs routes dynamically based on data acquired from deployed nodes, saving energy, time, and, ultimately money. In [55], an IoT system based on the LoRa network is deployed and evaluated for feasibility in the development of an economically viable digital waste management system for Industry 4.0 and smart cities. As identified in this work, the primary challenge to successful commercialization is the cost of the sensor accessories, which is essentially driven by the ultrasonic distance sensing portion, where dependable waterproof sensors suitable for outdoor circumstances are expensive to deploy via the LoRa network. A LoRaWAN-based solid waste management system with an energy harvesting sensor node is presented in [56]. The real-time deployment of the proposed architecture is performed and various evaluation metrics are provided to prove the feasibility of the work. In addition, an intelligent user interface is developed to locate the bins according to the filled levels. An architecture for building and developing a customized sensor node and gateway based on LoRa technology for accurately determining the filled level of bins is presented in [57]. This work evaluated the architecture's energy consumption by simulating it using the Framework for LoRa (FLoRa) simulation while adjusting several essential LoRa communication parameters.