Machine learning for internet of things classification using network traffic parameters

With the growth of the internet of things (IoT) smart objects, managing these objects becomes a very important challenge, to know the total number of interconnected objects on a heterogeneous network, and if they are functioning correctly; the use of IoT objects can have advantages in terms of comfort, efficiency, and cost. In this context, the identification of IoT objects is the first step to help owners manage them and ensure the security of their IoT environments such as smart homes, smart buildings, or smart cities. In this paper, to meet the need for IoT object identification, we have deployed an intelligent environment to collect all network traffic traces based on a diverse list of IoT in real-time conditions. In the exploratory phase of this traffic, we have developed learning models capable of identifying and classifying connected IoT objects in our environment. We have applied the six supervised machine learning algorithms: support vector machine, decision tree (DT), random forest (RF), k-nearest neighbors, naive Bayes, and stochastic gradient descent classifier. Finally, the experimental results indicate that the DT and RF models proved to be the most effective and demonstrate an accuracy of 97.72% on the analysis of network traffic data and more particularly information contained in network protocols. Most IoT objects are identified and classified with an accuracy of 99.21%

Coordinated Signal Control System in Urban Road Network

Road congestion has become one of the major problems of urban cities due to the growth in the number of vehicles and the limitation of road infrastructure. The consequences of this congestion can be seen through a difficult movement of vehicles, an increase in CO2 emissions, increasing energy consumption, and stress for drivers. Intelligent Transport Systems (ITS) based on wireless sensor networks (WSN) have emerged with new solutions and application potentials in the context of the Intelligent city.  In this article, we study an approach of using a wireless sensor network to control the traffic lights of several intersections and optimize their performance by reducing the average waiting time of users. the proposed adaptive traffic light controller determines the traffic lights sequence in real time based on the current traffic situation at the local intersection, the expected arrivals and the degree of congestion at destination intersections. To evaluate our approach, we construct an intersection network of twenty-four intersections with high traffic intensity using the SUMO simulator, the results of the simulation demonstrate the efficiency and practicality of the proposed algorithm

Overview of E-learning Platforms for Teaching and Learning

Distance learning experiments have been launched since 2010 in several Moroccan universities as part of an experimental approach. It, therefore, seems to us that a strategy must be put in place to give this choice of education its place in training and grant it the means necessary to achieve these objectives. The objective of this paper has presented an overview, of free and proprietary e-learning platforms, their functional architectures, as well as the types of e-learning devices that can create from platforms e-learning. To deduce the state of the art of the e-learning provisions of Moroccan universities and compare them with the e-learning provisions of European and American universities

Designing the Self-Management Space of a New Smart Learning Management System

This work is mainly based on designing an IMS-LD model for self-management space for a new LMS. Our work is first to think about the conditions for creating a real LMS between learners and teachers. we try to adapt the IMS-LD model with a self-management model based on the hybridization between four learning theories as to the basis for teaching this LMS, namely traditional pedagogy, behaviorism, cognitivism, and social constructivism. These pedagogies have already proven themselves, mainly in classroom learning situations

Coordinated Signal Control System in Urban Road Network

Road congestion has become one of the major problems of urban cities due to the growth in the number of vehicles and the limitation of road infrastructure. The consequences of this congestion can be seen through a difficult movement of vehicles, an increase in CO2 emissions, increasing energy consumption, and stress for drivers. Intelligent Transport Systems (ITS) based on wireless sensor networks (WSN) have emerged with new solutions and application potentials in the context of the Intelligent city.  In this article, we study an approach of using a wireless sensor network to control the traffic lights of several intersections and optimize their performance by reducing the average waiting time of users. the proposed adaptive traffic light controller determines the traffic lights sequence in real time based on the current traffic situation at the local intersection, the expected arrivals and the degree of congestion at destination intersections. To evaluate our approach, we construct an intersection network of twenty-four intersections with high traffic intensity using the SUMO simulator, the results of the simulation demonstrate the efficiency and practicality of the proposed algorithm

Overview of E-learning Platforms for Teaching and Learning

Distance learning experiments have been launched since 2010 in several Moroccan universities as part of an experimental approach. It, therefore, seems to us that a strategy must be put in place to give this choice of education its place in training and grant it the means necessary to achieve these objectives. The objective of this paper has presented an overview, of free and proprietary e-learning platforms, their functional architectures, as well as the types of e-learning devices that can create from platforms e-learning. To deduce the state of the art of the e-learning provisions of Moroccan universities and compare them with the e-learning provisions of European and American universities.</p

Ant Colony Optimization for Real Time Traffic Lights Control on a Single Intersection

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers

Generate a Meta-Model Content for Collaboration Space of Learning Management System Compatible with IMS-LD

The context of this work is that of designing a Instructional Management Systems - Learning Design (IMS-LD) model for collaboration space of a Learning Management System (LMS). Our work is specifically in the field or seeking to promote, by means of information technology from a distance. Our approach is to first think about the conditions for creating a real collaboration space between learners, and designing the IT environment that supports this space. In this paper, we try to adapt the IMS-LD model with a collaboration model for Learning Management System based on the social constructivism. This adaptation will go through three stages. Firstly, the development of an LMS model. Secondly, the study of correspondence between the developed model and IMS-LD model. Finally their transformation to IMS-LD model