Abstract— networking with the help of which real-world objects

 Abstract— Technical skills and knowledge gaining are takencare in today’s learning scenario. Internet of Things (IoT) refers, totechnological advancements in the networking with the help of which real-worldentities can be connected to communicate with each other over the internet. Ingeneral, replacing the teacher or giving quick instruction is not the goal nowadays.To do so,  academic institutes should investigatethe future technologies that comes out.  An IoTs enabled classroom, or Personal PC iswithout question adequately equipped to provide made-to-measure learning forstudents with individual needs, interactive learning experiences, fasterfeedback, easy collaboration access for both students and teachers andfacilitation for remote learning. The efficiency and cost benefits from anadministrative point of view are also enormous. In this paper, it will discussthe study the impact and model of IoT based e-Learning system refer totechnological advancements in the networking with the help of which real-worldobjects can be connected to communicate with each other over the internet andalso conclude how machine learning algorithms enhance the performance of IoT enabledE-learning system.  Keywords—IoT, applications of IoT, e-learning, IoTarchitecture, ubiquitous learning                                                                                                                                                               I.

          Introduction Some of the modern IoT artilleryin this domain includes digital highlighters, smarter boards. It means theprinted text could be digitally conveyed to the smartphone or any other app atan incredible speed through tools like Scan marker and c-pen. Interactiveboards can get, acknowledge, and reciprocate data, simplifying and stimulatingthe overall learning activity. Just imagine an outline where students sittingin a classroom or front of PC at their home can interact with their friends,classmates, teachers, and educators scattered over the world. Now, let’ssuppose the lesson of the day has focused on sea life. To give students anespecially exciting – and profoundly educational – experience, the mentordecides to access live information caused by sensors and live feeds monitoringa particular body of water.

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The IoT refers to a better vision whereby ‘things'(objects) such as everyday objects (entity), places, and environments haveinterconnected with one another via the Internet. An example of a simple IoTobject now available in some homes is a thermostat which can determine whenpeople occupy certain rooms and alter levels of heating, lighting and otherfunctions in the house accordingly. By widening the Internet from “a network ofinterconnected computers to a network of interconnected objects,” the IoT willcover a vast and complex network of devices. These devices will add sensors tomeasure the data of environment around them, actuators which physically actback into their environment such as processors to handle, opening the door andstore the massive data generated, nodes to send the information and organizersto help manage sets of these parts. Through this, it has the potential tosignificantly extend, enrich and even shift the relationship between people andthe world around them.

In fact, many are hoping that the IoT will play apivotal role in addressing many of today’s societal challenges such as an agingsociety, deforestation, traffic congestion and recyclability. Thisinterconnection of physical objects is expected to magnify the profoundconsequences that large-scale networked connections are having on our organization,gradually resulting in a genuine paradigm shift 1. In this paper, it has beenreview recent E-Learning-related literature associated with the IoT vision. Oneaim is to provide a resource for the E-learners to understand the current stateof research associated with the new IoT agenda.                                                                                                                                                              II.        Related Work In this section, some of the earlier works on thesubjects have cited.

According to Cisco 2, the organizations have alreadyexperienced the Internet of Things (IoT) – the networked connection of things, soonsome capabilities like context awareness, energy independence, and increasedprocessing power are added to these things then IoT becomes IoE (Internet of Everything). Also, according to their research, 99.4 percent ofphysical objects which can be a part of IoE is yet to be connected 3. Thewhitepaper concludes by saying, “There is tremendous value in connecting theunconnected with intelligent networks across education. This paper demonstratesIoE’s potential impact on making education more relevant, engaging andmotivating learners, and enabling faster time to mastery. However, to realizethe benefits of connecting people, processes, data, and things, reliableconnectivity and continuous access must be guaranteed. Additionally for IoE tobe accepted, both policymakers and educators must be well-prepared not only toexploit but also to understand potential risks.

” IoT will enable life-enhancingservices, regarding the role of IoT in education say, “In education,mobile-enabled solutions will tailor the learning process to each student’sneeds, improving overall proficiency levels, while linking virtual and physicalclassrooms to make learning more convenient and accessible 4. IoT might serveas the backbone for the universal learning environment and enable active smartenvironments to accept and identify objects and retrieve information from theinternet to facilitate their adaptive functionality 5. A learner may gain theknowledge not only by connecting to the learning contents via networks by usingdesktop computers or wireless handheld devices such as Personal DigitalAssistants (PDAs) and mobile phones but also by communicating to themicroprocessors (e.g.

, RFID – Radio Frequency Identification) embedded indevices.” In the reference paperR, two groups 25 students each were enrolledin a similar course. However, one group was taught using traditional methodsand other using an interactive system of the internet of things. Afterconducting various tests and analysis, they concluded that “Internet ofObjects, applied as a tool to support the teaching process, improves studentacademic performance”.  III.       IoT ENABLED APPLICATIONSThe following table 1 represents the relatedworks done on the IoT enabled applications for different domains.

Table 1:Related works done on the IoT enabled applications in different domains Authors Title of the paper Application Description Theodoridis, Evangelos, Georgios Mylonas, and Ioannis Chatzigiannakis 6 Developing an iot smart city framework Smart city Monitoring of parking spaces availability in the city. Noel, Adam, et al 7 Structural Health Monitoring using Wireless Sensor Networks: A Comprehensive Survey Structural health Monitoring of vibrations and material conditions in buildings, bridges and historical monuments. Majumder, AKM Jahangir A., et al 8 A wireless IoT system towards gait detection in stroke patients Smartphone Detection Detect iPhone and Android devices and in general any device which works with WiFi or Bluetooth interfaces. Ozger, Mustafa, Oktay Cetinkaya, and Ozgur B. Akan 9 Energy Harvesting Cognitive Radio Networking for IoT-enabled Smart Grid Electromagnetic Field Levels Measurement of the energy radiated by cell stations and WiFi routers.

Jeyasheeli, P. Golda, and JV Johnson Selva 10 An IOT design for smart lighting in green buildings based on environmental factors Smart Lighting Intelligent and weather adaptive lighting in street lights. Keerthana, B., et al11 Internet of Bins: Trash Management in India Waste Management Detection of rubbish levels in containers to optimize the trash collection routes.

Shaikh, Faisal Karim, Sherali Zeadally, and Ernesto Exposito12 Enabling technologies for green internet of things Forest Fire Detection Monitoring of combustion gases and preemptive fire conditions to define alert zones. Obara, Kazushige, et al13 A densely distributed high-sensitivity seismograph network in Japan Earthquake Early Detection Distributed control in specific places of tremors. Weidhaas, Jennifer, Lian-Shin Lin, and Karen Buzby 14 A case study for orphaned chemicals: 4-methylcyclohexanemethanol (MCHM) and propylene glycol phenyl ether (PPH) in riverine sediment and water treatment processes. Chemical leakage detection in rivers Detect leakages and wastes of factories in rivers. Gupta, Shikha Pranesh, and Umesh Kumar Pandey 15 Automatic and Intelligent Integrated System for Leakage Detection in Pipes for Water Distribution Network Using Internet of Things Water Leakages Detection of liquid presence outside tanks and pressure variations along pipes. El-Din, Hemdan Ezz, and D.

H. Manjaiah 16 Internet of Nano Things and Industrial Internet of Things M2M Applications Machine auto-diagnosis and assets control. Tsai, Yao-Te, et al 17 Precise Positioning of Marketing and Behavior Intentions of Location-Based Mobile Commerce in the Internet of Things Intelligent Shopping Applications Getting advices in the point of sale according to customer habits, preferences, presence of allergic components for them or expiring dates. Tao, Fei, et al 18 Internet of Things in product life-cycle energy management Smart Grid Energy consumption monitoring and management. Veeramanickam, M. R. M., and M.

Mohanapriya 19 IOT enabled Futurus Smart Campus with effective E-Learning: i-Campus E-learning  In digital era our College campus need of IoT technology for classy environment to utilize  effective E-learning. Auer, Michael E., and Danilo G. Zutin, eds 20 Online Engineering & Internet of Things: Proceedings of the 14th International Conference on Remote Engineering and Virtual Instrumentation REV 2017 Smart E-learning IoT technology for classy environment to utilize  effective E-learning                                                                                                                                    IV.       The  IoT Enabled E-LEARNING E-learning is currently implemented using various techniques and technologies.Some technologies (Some of Listed in Table 1) have been specifically developedfor the same while others can be used as successful E-learning tools. SomeTechnologies used in E-learning are:Table 2: Related works done on IoT enabled E-Learning  Authors Title of the paper Keywords Description Bystrova, T.

Yu. Larionova, V. A. Osborne, M. Platonov, A. M. 21 Introduction of open e-learning system as a factor of regional development Information society Educational paradigm Regional development Lifelong learning E-learning Open e-learning Educational resources Massive open online course Nancial model Economic efect The description is made of the cost options for open-type e-learning course development, investment parameters for their establishment, as well as costs of implementing educational programmes with the application of e-learning.

The analysis of the activities of Ural Federal University on implementing e-learning gives the opportunity to further imagine the effect from the introduction of e-learning in other universities in the region. Islam, Nurul, Martin Beer, and Frances Slack 22 E-learning challenges faced by academics in higher education: a literature review e-learning, higher education, academic challenges, e-learning in Middlesex Universit This paper references some of the research work on the limitations of e-learning technology, categorises it in five challenges that teachers are faced with and suggestions for a successful e-learning outcome. This paper also discusses the use of e-learning technology in Middlesex University and some of the challenges they face. Kong, Siu Cheung, et al 23 E-learning in School Education in the Coming 10 Years for Developing 21st Century Skills: Critical Research Issues and Policy Implications E-Learning, School education, 21 st century skils, Research issues, Policy implications This paper aims to discuss the research issues and policy implications critical for achieving such a curriculum goal. A review of literature in the related fields indicates that K-12 schools should take advantage of e-learning to maximize learning opportunities of learners for the development of 21st century skills. Charmonman, Srisakdi, et al 24 e-Learning and the Science of Instruction: Proven Guidelines for Consumers and Designers of Multimedia Learning Educational paradigm Regional development Lifelong learning E-learning Open e-learning   e-Learning and the Science of Instruction is the ultimate handbook for evidence-based e-learning design.

Since the first edition of this book, e-learning has grown to account for at least 40% of all training delivery media. However, digital courses often fail to reach their potential for learning effectiveness and efficiency. Charmonman, Srisakdi, et al 25 Applications of Internet of Things in E-Learning Internet of Things, IoT in eLearning, IoT and instructional design, IoT and training, Skills for IoT, Internet of Learning Things, IoT to transform education, IoT to improve student performance This paper will discuss IoT in eLearning and instructional design, training employees on IoT technology, six skills for IoT applications, Internet of Learning Things, IoT potentials to transform education, and IoT to improve student performance                                                                                                                         V.        Machine Learning Algorithms in IoTThe following table 3depicts the related works done in IoT by using Machine Learning algorithms.

Table 3: Related Works doneon IoT using Machine Learning algorithms  Authors Title of the paper Keywords Description Zou, Han, et al 26 A fast and precise indoor localization algorithm based on an online sequential extreme learning machine Biomedical monitoring, Biomedical monitoring, Sensors, Medical services, Smart homes, Logic gates, Assisted living, Ambient networks, Internet of things This article differs from seamlessly linking multimodel data-collecting infrastructure and data analytics together in an AAL platform. This article also outlines a multimodality sensor platform with heterogeneous network connectivity, which is under development in the sensor platform for healthcare in a residential environment (SPHERE) Interdisciplinary Research Collaboration (IRC). Lane, Nicholas D., et al 27 An early resource characterization of deep learning on wearables, smartphones and internet-of-things devices behavior and ambient context, IoT, Deep Learning, smartphones, wearable systems.

The aim of this investigation is to begin to build knowledge of the performance characteristics, resource requirements and the execution bottlenecks for deep learning models when being used to recognize categories of behavior and context. Zou, Han, et al 28 An online sequential extreme learning machine approach to WiFi based indoor positioning IEEE 802.11 Standards, Calibration, Training, Accuracy, Testing, Mathematical model, Heuristic algorithms An indoor localization algorithm based on online sequential extreme learning machine (OS-ELM) to address these problems accordingly Alsheikh, Mohammad Abu, et al 29 Machine learning in wireless sensor networks: Algorithms, strategies, and applications Wireless sensor networks, Routing, Machine learning algorithms, Clustering algorithms, Algorithm design and analysis, Principal component analysis, Classification algorithms An extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in WSNs. The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. Lane, Nicholas D., et al 30 A large-scale web QoS prediction scheme for the Industrial Internet of Things based on a kernel machine learning algorithm   Kernel least mean square Quality of services (QoS) QoS prediction Pearson correlation coefficient (PCC) Industrial Internet of Things (IIoT)   Apply the derived coefficients for the prediction of missing web service QoS values. An extensive performance study based on a public data set is conducted to verify the prediction accuracy of our proposed scheme                                                                                                                                                               VI.       CONCLUSIONInternet of Things (IoT)already delivers connectivity to a broad range of devices, enabling thedevelopment of innovative new services and applications.

In the field ofeducation, IoT will take E-learning to the next level. This paper explains therelated works done on the implementation of IoT in different domains and theapplications that are utilizing IoT. And the detailed description of the workdone on IoT based E-Learning system and the IoT using Machine Learningalgorithms. In the future, this IoT based E-learning can leverage the power ofIoT to implement a smart learning environment that facilitates better learningand higher retention rates. This advancement in education to produce betterindividuals regarding skills and knowledge.