CityMii - An integration and interoperable middleware to manage a Smart City

Modern cities are supported by multiple heterogeneous IT systems deployed and managed by distinct agents. In general, those systems use old, dependent and non-standardized technologies, which make them legacy and incompatible systems. As smart cities are moving toward a fully centralized management approach, the lack of integration among systems raises several problems. Since they are independent, it is not easy to correlate information from different systems and put it together to work in order to achieve application goals. The collaboration among different systems enables an agent to offer new functionalities (services or just information about the city) that cannot be provided by any of these systems working as individual entities. The goal of this paper is to propose an integration middleware to support the management of Smart Cities in a dynamic, transparent and scalable way. The proposed middleware intends to support interoperability among different systems operating in a city.info:eu-repo/semantics/publishedVersio

Analysis of Soil Nitrate Ion Selective Electrode (ISE) Sensor using Arduino UNO

The ecological concern over soil and groundwater pollution caused by agricultural activities has led to the growing interest in precision agriculture. One of the most common types of fertilizer is the nitrogen fertilizer which needed in major amount for plant growth. Over fertilization will contaminate soil and groundwater which can have adverse effect on environment and human health. The main purpose of this research is to measure soil nitrate concentration using nitrate ion-selective electrode (ISE) sensor and Arduino programmable microcontroller. The optimum soil-to-water ratio and the effect of soil solution clarity will be investigated. Standard sampling procedures was conducted at oil palm plantation area, Felda Bukit Goh, Pahang, Malaysia. Validation of the results were carried out in the laboratory. The recorded data indicated accurate readings for Nitrate ISE Arduino was R² = 0.84. The soil-to-water ratio of 1:2.5 was observed as an optimal proportion ISE analysis. A clear soil solution was crucial for maintaining the accuracy of ISE sensor, to avoid declining of 46.2% accuracy. These results could assist researchers and farmers to accurately monitor the concentrations of soil nitrate on the field effectively as well as an insight to ISE sensor with Arduino technologies

Sistema de gerenciamento de dados para análise de solos por espectroscopia molecular

Atualmente a identificação da maioria dos elementos encontrados no solo possuem métodos de análise atualizados e eficientes, porém a quantificação de matéria orgânica ainda é realizada através de métodos morosos e que resultam em grande quantidade de resíduos químicos. Desta maneira, surge a necessidade de tornar essa análise mais ágil e sustentável. Nos últimos tempos, o uso da espectroscopia molecular associada à quimiometria tem se destacado na avaliação qualitativa e quantitativa de diferentes tipos de materiais. Assim, o objetivo deste trabalho foi o desenvolvimento de um software, que a partir dos espectros infravermelhos das amostras de solo, seja capaz de analisar e gerar um modelo preditivo para amostras futuras, reduzindo o tempo de análise e a geração de resíduos. O software foi desenvolvido num ambiente de desenvolvimento integrado (IDE, Integrated Development Environment) cuja função é reunir características e ferramentas de apoio à construção de sistemas. Para isso, utilizou-se a IDE Microsoft Visual Studio 2015, versão Profissional, com alto nível de abstração de controles e classes, incluindo bibliotecas para gráficos. Além de eficiente, o Software mostrou-se capaz de analisar amostras de forma rápida e com pequena variação de resultados gerados por métodos atuais, permitindo o armazenamento das informações coletadas para criação de sistemas de predição

Quality management of surveillance multimedia streams via federated SDN controllers in Fiwi-iot integrated deployment environments

Traditionally, hybrid optical-wireless networks (Fiber-Wireless - FiWi domain) and last-mile Internet of Things edge networks (Edge IoT domain) have been considered independently, with no synergic management solutions. On the one hand, FiWi has primarily focused on high-bandwidth and low-latency access to cellular-equipped nodes. On the other hand, Edge IoT has mainly aimed at effective dispatching of sensor/actuator data among (possibly opportunistic) nodes, by using direct peer-to-peer and base station (BS)-assisted Internet communications. The paper originally proposes a model and an architecture that loosely federate FiWi and Edge IoT domains based on the interaction of FiWi and Edge IoT software defined networking controllers: The primary idea is that our federated controllers can seldom exchange monitoring data and control hints the one with the other, thus mutually enhancing their capability of end-to-end quality-aware packet management. To show the applicability and the effectiveness of the approach, our original proposal is applied to the notable example of multimedia stream provisioning from surveillance cameras deployed in the Edge IoT domain to both an infrastructure-side server and spontaneously interconnected mobile smartphones; our solution is able to tune the BS behavior of the FiWi domain and to reroute/prioritize traffic in the Edge IoT domain, with the final goal to reduce latency. In addition, the reported application case shows the capability of our solution of joint and coordinated exploitation of resources in FiWi and Edge IoT domains, with performance results that highlight its benefits in terms of efficiency and responsiveness

Detection of Soil Nitrogen Using Near Infrared Sensors Based on Soil Pretreatment and Algorithms

Soil nitrogen content is one of the important growth nutrient parameters of crops. It is a prerequisite for scientific fertilization to accurately grasp soil nutrient information in precision agriculture. The information about nutrients such as nitrogen in the soil can be obtained quickly by using a near-infrared sensor. The data can be analyzed in the detection process, which is nondestructive and non-polluting. In order to investigate the effect of soil pretreatment on nitrogen content by near infrared sensor, 16 nitrogen concentrations were mixed with soil and the soil samples were divided into three groups with different pretreatment. The first group of soil samples with strict pretreatment were dried, ground, sieved and pressed. The second group of soil samples were dried and ground. The third group of soil samples were simply dried. Three linear different modeling methods are used to analyze the spectrum, including partial least squares (PLS), uninformative variable elimination (UVE), competitive adaptive reweighted algorithm (CARS). The model of nonlinear partial least squares which supports vector machine (LS-SVM) is also used to analyze the soil reflectance spectrum. The results show that the soil samples with strict pretreatment have the best accuracy in predicting nitrogen content by near-infrared sensor, and the pretreatment method is suitable for practical application