Challenges and Opportunities of Waste Management in IoT-enabled Smart Cities: A Survey
Abstract:
The new era of Web and Internet of Things(IoT)paradigm is being enabled bythe proliferation of various devices like RFIDs, sensors, and actuators. mart devices(devices having significant computational capabilities, transforming them to ‘smart things’)are embedded in the environment to monitor and collect ambient information. In a city, this leads to Smart City frameworks. Intelligent services could be offered on top of such information related to any aspect of humans’ activities. A typical example of services offered in the framework of SmartCities is IoT-enabled waste management. Waste management involves not only the collection of the waste in the field but also the transport and disposal to the appropriate locations. In this paper,we present a comprehensive and thorough survey of ICT-enabledwaste managementmodels. Specifically, we focus on the adoption of smart devices as a key enabling technology in contemporary waste management. We report on the strengths and weaknesses of various models to reveal their characteristics. This survey sets up the basis for delivering new models in the domain as it reveals the needs for defining novel frameworksfor waste management.
Existing system:
The adoption of Future Internet technologies enhanced by the use of the Internet Protocol (IP)on numerous wireless sensors enables the Internet of Things (IoT)paradigm. Numerous sensors have the opportunity to be part of Wireless Sensor Networks (WSNs). When WSNs are applied in a city, they are responsible for collecting and processing ambient information and, thus, to upgrade legacy city infrastructure to the so-called Smart Cities (SCs).A definition of the concept of SC is provided in[6]: “A Smart City is a city well performing in a forward-looking way in the following fundamental components (i.e., Smart Economy, Smart Mobility, Smart Environment, Smart People, Smart Living, and Smart Governance), built on the ‘smart’ combination of endowments and activities of self-decisive, independent and aware citizens”. This definition incorporates the fundamental component of a smart environment which is mainly adopted for systems dealing with environmental pollution. The concept of smart environments depicts the ambient intelligence found in a SC through the adoption of smart devices and wireless networks. This way, intelligent applications could be delivered on top of such infrastructures. WSNs are capable of reforming activities in a SC in every aspect of daily life[3]. In this paper, we focus on a specific application domain, waste management. The efficient management of waste has a significant impact on the quality of life of citizens. The reason is that waste disposal has a clear connection with negative impacts in the environment and thus on citizens’ health.
Proposed system:
The current survey focuses onresearch approaches that incorporate modern ICTtechniques and tools in SCs. The adoption of ICT technologies is depicted inour taxonomy.We report on the proposed taxonomy before we survey the existing research efforts to give the readers the necessary overview of the domain. Hence, the interested readers will be capable of easily identify the main characteristics of each model and their place in the respective literature. We define the concept of waste management context that aims to setup the basis for classifying waste management models. The waste management context incorporates the hardware, tools, data and software that a waste management model adopts to become the basis for realizing a waste management solution. In general, the waste management context could be categorized in three main categories: (i) the physical infrastructure, (ii) the IoT Technology, and (iii)the software analytics. These categories are discrete which means that the relevant context of each model belongs only to one of the aforementioned categories. Our taxonomy is organized concretely (i.e., we pay attention not only to the infrastructure but also to the data and the required software)to coverage range of diverse components and features. Each contextual component and feature is assigned specific values denoting its rational existence in the proposed taxonomy. Components are related to the tools / hardware adopted in each category while features are related to the contextual information (e.g., data)adopted in each category / model.
Conclusion:
This survey’s focus is on more energy-efficient IoT as an enabler of various applications including waste management. Specifically, itaims to present a large set of models dealing with the efficient waste management. Special attention is paid on the waste collection. We present efforts for theintelligent transportation within the context of IoT and Smart Cities for waste collection. We propose an inductive taxonomy to perform comparative assessment of the surveyed models. We focus only on effortsthat incorporate ICTmodelsfor waste collection in SC. We deliver the strengths and weaknesses of the surveyed models. Finally, our future work is focused on the definition of an effective IoT-enabled model for waste collection, which will touch on the in corporation f high capacity waste trucks as mobile depots. In addition, waste bins are placed to optimize comfort of residents. However, as part of the future work we will be looking at bin connectivity constraints that may affect their placement, for example, the output power of a communicating sensor would need to be set too high which may drain the battery faster. In this case, the bin may be placed somewhere where energy consumption is more efficient.
References:
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