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Adaptive meta-heuristics with automatic calibration parameters for developing a planning and management municipal services system, integrated with geo-location and mobile devices


In General cities do not have computerized systems to attend municipal services, such as maintenance and pruning of trees, maintenance of public roads, special waste removal, cleaning of drains and other. For the most part, the Municipal Services departments receive the service demands of the population through telephone calls. For proper planning, many factors need to be taken into consideration, such as prioritization as the urgency of care, distance and time, time to perform the task and ability of daily attendance, it is not possible for a human operator to perform all the analyses necessary for the definition of the best planning. In addition, in emergency situations, such as events of heavy rain causing flooding and fallen trees, the urgent demands of population compete with the usual demands, worsening the efficiency of customer service. Concerning this topic, the Geoambiente developed in 2015, an answering system and dispatch teams to the HUGE energy, energy distribution company in the State of Rio de Janeiro; the system combines heuristic modeling and geolocation, calculating routes and optimized computing attendances and services teams. The system had great impact in improving attendance among the customers of the company. Analyzing the situation of medium-to large-sized cities, we identified that the system developed for the electricity sector can be improved and adapted to meet the municipal services, but to ensure its success, there is a need to define automated algorithm parameters for its implementation. This is because, in the cities and in the service to municipal services, it is necessary to use different parameters depending on the input data and, in most cases, the city officials don't have the preparation of engineering required for the calibration of input parameters for the operating system; in this way, with this improvement in the software, the decision maker would not need to worry about parameterize the system according to the changes of the input data (daily or in specific situations of emergency) because the intended algorithm adapts during the search process. This research Project is focused on:the development of a hybrid method that is efficient and robust for the needs of service management of the municipal services of automation calibration of parameters of method execution, with the introduction of algorithms for automatic calibration of each instance runs. This technology aims to provide automatic parameterization of the system, according to the changes of scenery present in everyday life and especially in crisis scenarios, being this one of the scientific challenges of the project. It is intended that the developed system can be widely used for any city in the country, without requiring great effort for their calibration and without the need for skilled labor in the municipality. The integration with Google's database, will contribute to the widespread use of the system, because all the towns are covered by this database; the offer of software as a service (SaaS), facilitate their acquisition by prefectures of various sizes, because the pay will be defined in accordance with the use; interaction with mobile devices, combined with the auto-parameterization of the system, will enable near real-time interaction with the citizen and customer service emergency requests. All these points contribute to the economy of resources of the prefectures, the efficiency in meeting demands of population and its insertion in the concept of smart cities (AU)

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