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      Smart Waste Collection System with Low Consumption LoRaWAN Nodes and Route Optimization

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          Abstract

          New solutions for managing waste have emerged due to the rise of Smart Cities and the Internet of Things. These solutions can also be applied in rural environments, but they require the deployment of a low cost and low consumption sensor network which can be used by different applications. Wireless technologies such as LoRa and low consumption microcontrollers, such as the SAM L21 family make the implementation and deployment of this kind of sensor network possible. This paper introduces a waste monitoring and management platform used in rural environments. A prototype of a low consumption wireless node is developed to obtain measurements of the weight, filling volume and temperature of a waste container. This monitoring allows the progressive filling data of every town container to be gathered and analysed as well as creating alerts in case of incidence. The platform features a module for optimising waste collection routes. This module dynamically generates routes from data obtained through the deployed nodes to save energy, time and consequently, costs. It also features a mobile application for the collection fleet which guides every driver through the best route—previously calculated for each journey. This paper presents a case study performed in the region of Salamanca to evaluate the efficiency and the viability of the system’s implementation. Data used for this case study come from open data sources, the report of the Castilla y León waste management plan and data from public tender procedures in the region of Salamanca. The results of the case study show a developed node with a great lifetime of operation, a large coverage with small deployment of antennas in the region, and a route optimization system which uses weight and volume measured by the node, and provides savings in cost, time and workforce compared to a static collection route approach.

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          The Truck Dispatching Problem

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            Towards sustainable smart cities: A review of trends, architectures, components, and open challenges in smart cities

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              A comparative study of LPWAN technologies for large-scale IoT deployment

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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                08 May 2018
                May 2018
                : 18
                : 5
                : 1465
                Affiliations
                [1 ]Faculty of Science, University of Salamanca, Plaza de la Merced s/n, 37002 Salamanca, Spain; jch@ 123456usal.es (J.C.); fcofds@ 123456usal.es (J.F.D.P.); gvg@ 123456usal.es (G.V.G.)
                [2 ]Department of Artificial Intelligence, Polytechnic University of Madrid, Campus Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain; jbajo@ 123456fi.upm.es
                Author notes
                [* ]Correspondence: loza@ 123456usal.es ; Tel.: +34-64-6891-785
                Author information
                https://orcid.org/0000-0002-0493-4471
                https://orcid.org/0000-0002-0020-827X
                https://orcid.org/0000-0002-6536-2251
                https://orcid.org/0000-0002-4392-4743
                Article
                sensors-18-01465
                10.3390/s18051465
                5982603
                29738472
                56ef6338-81cb-451b-9683-67ae5a0b8635
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 22 March 2018
                : 02 May 2018
                Categories
                Article

                Biomedical engineering
                smart waste collection,low powered sensors,wireless sensor networks,data analytics,decision-making,lorawan,open data,vrp,cvrp

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