# Sensor-Based Solid Waste Handling Systems: A Survey
## 7 Research Gaps and Future Direction  
As far as waste management is concerned, it is a series of actions taken from the root to the final disposal of waste materials. The evolution of communication technologies and advancements in sensor designs revolutionized the conventional waste management system into an intelligent system. From the study performed on the various solid waste handling systems for smart cities, many research works present promising architecture and network models, which can be considered for real-time deployment. Nevertheless, this work identified some of the research gaps that need to be addressed for enhancing solid waste management in smart cities. This section describes various research gaps identified from the literature and the respective future directions to address the same. * Self-powered end nodes: IoT systems comprise a large number of end nodes and gateways or base stations; while the end nodes are deployed at various locations, the gateways or base stations gather the data from the end nodes and send it to the internet for further analysis. The end nodes are preferably powered with batteries, and the frequent replacement of batteries is impractical when considering the wide range deployment of nodes. Some works in the literature proposed energy harvesting by using solar panels to address this issue. Still, there is a large scope of systems that need to adopt advanced methodologies to enhance the design of IoT-enabled solid waste handling systems with self-powered end nodes:
* Edge computing enabled waste segregation: Currently, waste segregation is implemented by placing multi-colored or labeled bins for the easy classification of the waste material. Even if it is an easy method of collecting a particular kind of waste, this approach cannot always be successful because, by mistake, people may place waste in the wrong bins and it will disturb proper segregation. Nevertheless, waste segregation by the bin itself would be a solution. There is a solid research scope in the aforementioned scenario to design edge computing-enabled smart nodes incorporated with image processing techniques to implement waste segregation. * Hybrid network architecture: Waste generation is dynamic and varies concerning the environment. For instance, the frequency of filling of a trash bin installed at public places will be dynamic and the filling of trash bins installed at houses or residential areas will be probably in a uniform manner. From the survey performed on existing approaches, it is evident that LPWAN communication technologies are best suited for monitoring bins at public places since bins are deployed at distant locations. Similarly, short-range communication technologies such as Wi-Fi are best suited for monitoring trash bins located at houses since most houses will be equipped with a Wi-Fi router for internet connectivity. Nevertheless, none of the existing systems describe solid waste management models or network architectures for waste management in flats or apartments. Moreover, waste management in urban areas is incomplete without addressing the aforementioned scenario. As a result, a lot of research attention is required in developing hybrid network architectures that are capable to address the solid waste management requirements in public areas and residential areas differently. * Smart Transportation: Transportation plays a crucial role in an efficient waste management system. Most of the existing approaches send the trash bin status to the central monitoring station or cloud servers for performing data analysis. On the basis of this analysis, waste collection routes will be scheduled and a truck or waste collection vehicle shall follow this scheduled path for optimized waste collection. Meanwhile, an unscheduled trash bin may become completely filled and miss the pick up. Thus, there is a need for dynamic path optimization centered on the waste collection vehicles' live location and the real-time status of the trash bins.