Abstract
Long Range Wide Area Network (LoRaWAN) has rapidly become one of the key enabling technologies for the development of Internet of Things (IoT) architectures. A wide range of different solutions relying on this communication technology can be found in the literature: nevertheless, the most part of these architectures focus on single task systems. Conversely, the aim of this paper is to present the architecture of a LoRaWAN infrastructure gathering under the same network different typologies of services within one of the most significant sub-systems of the Smart City ecosystem (i.e., the Smart Waste Management). The proposed architecture exploits the whole range of different LoRaWAN classes, integrating nodes of growing complexity according to the different functions. The lowest level of this architecture is occupied by smart bins that simply collect data about their status. Moving on to upper levels, smart drop-off containers allow the interaction with users as well as the implementation of asynchronous downlink queries. At the top level, Video Surveillance Units (VSUs) are provided with machine learning capabilities for the detection of the presence of fire nearby bins or drop-off containers, thus fully implementing the Edge Computing paradigm. The proposed network infrastructure and its subsystems have been tested in a laboratory and in the field. This study has enhanced the readiness level of the proposed technology to Technology Readiness Level (TRL) 3.
Highlights
Waste production has gradually increased with the development of both urban centres and consumer society
Such trials were sorted out exploiting a smart drop-off container indoor installed within the laboratory: several filling levels (i.e., 0 cm, 20 cm, 40 cm, 60 cm, 80 cm and 100 cm) were reproduced within the dropoff container, 200 measurements were performed, sent via Long Range Wide Area Network (LoRaWAN) and stored in order to be analyzed
Since the precise knowledge of the filling level was not crucial in contrast with the awareness of the occurrence of the event associated to the need of depletion caused by the maximum filling level, the ultrasonic sensor may be deemed to be reliable for understating the happening of the latter event
Summary
Waste production has gradually increased with the development of both urban centres and consumer society. To render waste management systems efficient, it is important for the collection to keep the same pace as the generation. This enables municipalities to minimize the waste management costs and simultaneously facilitate recycling with separate collection schemes, which effectively reduce the environmental burden of waste (global warming, littering and so on). To this end, ad-hoc monitoring infrastructures may be set up for example to control filling level of public waste bins. Precise estimates, forecasts and control may be ensured enabling preventing maintenance, prompt decision making, optimization of bins depletion procedures and management and widespread enforcing so as to fight and forestall acts of vandalism and service misuses
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