Integration of AI and the IoT in Education: Comparison
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The emulation of human intelligence processes by computer systems is known as artificial intelligence (AI). The development of intelligent machines that function and respond much like people is the focus of this area of computer science. Machine learning, computer vision, and natural language processing are all examples of AI technology. These tools may be used to build systems with intelligence that can reason, analyze, and gain knowledge from data. On the other hand, the Internet of Things (IoT) is a network of real physical items, such as gadgets and appliances, that are integrated with sensors, software, and connections to allow for data collection and exchange. The integration of AI and the IoT in education has the potential to revolutionize the way we learn. Personalized learning, real-time feedback and support, and immersive learning experiences are some of the benefits that AI and the IoT can bring to the education system.

  • AI
  • IoT
  • sustainable education systems
  • smart cities

1. Introduction

Various scholars have worked to examine the application of AI- and IoT-assisted sustainable education systems during the pandemic. The use of artificial intelligence (AI) and the Internet of Things (IoT) in education has grown in popularity in recent years, with potential benefits, such as personalized learning and improved student engagement. However, the global COVID-19 pandemic accelerated the need for remote and online learning, leading to an increased interest in the use of AI and the IoT in educational systems for smart cities. One study explored the potential of AI-assisted education in smart cities during the COVID-19 pandemic [1]. The authors found that AI-assisted education can provide personalized and adaptive learning and support for remote and online learning. They also discussed the importance of data privacy and security in the implementation of AI-assisted education systems. Another study investigated the use of the IoT in educational systems for smart cities during the COVID-19 pandemic [2]. The authors found that IoT-assisted education can provide real-time monitoring and data collection and support for remote and online learning. They also discussed the challenges of implementing the IoT in education, such as cost and privacy concerns.
Moreover, Chakraborty and Abougreen [3] examined the use of AI and the IoT in a smart campus system during the COVID-19 pandemic. The authors found that a smart campus system can provide a range of benefits, such as real-time monitoring of students’ attendance and learning progress and support for remote and online learning. They also discussed the potential challenges of implementing such a system, such as data privacy and security. In a systematic review, ref. [4] analyzed the existing literature on the use of AI and the IoT in education during the COVID-19 pandemic. The authors found that AI- and IoT-assisted education can provide a range of benefits, such as personalized and adaptive learning, real-time monitoring and data collection, and support for remote and online learning. Another study also supported the claim regarding the potential challenges, such as data privacy and security, and the importance of further research to address these challenges in a smart city [5][6].
In terms of education, the study [6] states that AI and IoT technologies have been used to enable remote learning and online education. This includes the use of virtual and augmented reality, online tutoring, and e-learning platforms. The authors also note that AI and IoT technologies have been used to improve the accessibility of online education for students with disabilities. Additionally, the paper suggests that AI and IoT technologies have the potential to improve the efficiency and effectiveness of online education by providing personalized learning experiences and real-time feedback to students and teachers. However, the authors also note that there are still challenges to be addressed, such as the need for more robust and secure systems and the need for more research on the long-term effects of using these technologies in education. Succinctly, research on AI- and IoT-assisted education systems during pandemics, such as COVID-19, for smart cities indicates that these technologies can provide a range of benefits, such as personalized and adaptive learning, real-time monitoring and data collection, and support for remote and online learning. However, there are also potential challenges, such as data privacy and security, that need to be addressed in the implementation of these systems.

2. Future Vision of Artificial Intelligence- and Internet of Things-Assisted Education System

Artificial intelligence (AI) and the Internet of Things (IoT) have the potential to revolutionize the field of education by enhancing the learning experience and personalizing instruction [7]. The integration of these technologies into the education system can provide a more interactive, efficient, and engaging learning environment. One of the main ways AI can assist in education is through intelligent tutoring systems (ITSs) [8]. The future of AI and ITSs looks promising, as these technologies have the potential to revolutionize the way people learn. ITSs can use AI-powered algorithms to analyze student data and create personalized learning experiences for each student. This includes providing students with tailored content, assessments, and feedback that align with their unique learning style and pace. Additionally, ITSs can use natural language processing (NLP) and machine learning (ML) techniques to communicate with students in a more natural and human-like way, making the learning experience more engaging and interactive. These systems use AI techniques, such as natural language processing and machine learning, to adapt to each student’s individual needs and abilities. For example, the Carnegie Learning Cognitive Tutor uses AI to provide personalized feedback and instruction to students, resulting in improved performance and motivation [8].
Another area in which AI can assist in education is through the use of natural language processing and machine learning to automatically grade student work. This can save educators significant time and allow for a more efficient and accurate assessment of student learning [9]. This technology can potentially change how student work is automatically graded in the future. It can enhance the automated grading process through the use of smart cameras and microphones. IoT-enabled devices, such as smart cameras and microphones, can be used to assess student work in real time, providing instant feedback on their performance. For example, a smart camera could be used to monitor a student’s writing during an exam, providing instant feedback on their grammar and spelling. A microphone could be used to assess a student’s pronunciation in a language class and give instant feedback on specific sounds or words. IoT technology can also be used to facilitate remote monitoring and grading of student work [10]. For example, students can use IoT-enabled devices, such as laptops and tablets, to participate in remote classes, and teachers can use these devices to monitor and grade student work. This would be particularly useful for students who are not able to attend traditional classroom settings, such as those who are physically disabled or live in remote areas. IoT technology can also play a role in education by providing students with access to a wide range of digital resources and enabling collaboration and communication among students and teachers. For example, the use of IoT-enabled devices, such as smartphones, tablets, and smartboards, can allow for the creation of interactive and engaging learning experiences.
Furthermore, the IoT can be used to track and monitor student progress, providing teachers with real-time data on student engagement, performance, and learning outcomes. It can be used to track and monitor student progress by integrating smart devices into the classroom [11]. These devices can collect student engagement, performance, and behavior data, providing teachers and administrators with valuable insights into student progress. For example, IoT-enabled devices, such as smart cameras and microphones, can be used to track student engagement during class, providing teachers with real-time feedback on student participation and attention levels. IoT-enabled devices, such as tablets and laptops, can be used to track student performance on assessments and homework assignments, providing teachers with a complete picture of student progress. This can be used to personalize instruction, identify areas of difficulty, and adjust teaching methods as needed [11]. Succinctly, the integration of AI and the IoT in the education system has the potential to provide a more personalized, interactive, and efficient learning experience. However, it is important to consider the ethical and privacy concerns associated with using these technologies, as well as the need for proper training for educators to fully realize their potential.
One of the main ways AI can assist in education during pandemics is through virtual and remote learning systems. AI-powered virtual learning environments (VLEs) can provide students with personalized, self-paced instruction and adapt to the individual needs of each student [12]. Additionally, AI-powered virtual assistants can provide students with real-time support and guidance, helping to mitigate the lack of face-to-face interaction with teachers [13]. IoT technology can also play a role in education during pandemics by providing students with access to a wide range of digital resources and enabling remote collaboration and communication among students and teachers. IoT-enabled devices, such as smartphones, tablets, and smartboards, can be used to create interactive and engaging learning experiences, even in a remote setting. IoT-enabled monitoring of students’ activity and progress can also provide teachers with real-time data on student engagement, performance, and learning outcomes. This can be used to personalize instruction, identify areas of difficulty, and adjust teaching methods as needed.
AI and the IoT can also be used to create intelligent personal learning environments (PLEs) that can adapt to each student’s unique needs and preferences and provide real-time feedback and guidance, helping to improve student engagement and learning outcomes [14]. A PLE is a personalized and adaptive learning environment that uses AI and the IoT to provide students with a tailored learning experience. The two most prominent anticipated future visions of incorporating AI and IoT technologies based on PLEs include providing personalized content and adaptive learning. AI can be used to analyze student data and create personalized content that aligns with their unique learning style and pace. For example, an AI-powered learning management system (LMS) could provide students with tailored content based on their performance on assessments and homework assignments. IoT-enabled devices, such as smart cameras and microphones, can be used to monitor student engagement and provide real-time feedback. AI algorithms can then use these data to adapt the learning experience in real time. For example, if a student is struggling with a particular concept, the PLE can provide them with additional resources or support to help them better understand the material. Furthermore, AI-powered virtual and augmented reality technologies can also create immersive and interactive learning experiences, even in a remote setting [15].
In conclusion, AI and the IoT have the potential to transform education in the context of pandemics by providing a more flexible and adaptable learning environment. The integration of these technologies can provide students with personalized instruction, real-time support and guidance, and access to a wide range of digital resources. However, it is important to consider the ethical and privacy concerns associated with using these technologies, as well as the need for proper training for educators to fully realize their potential. The Table 1 below shows the future vision of AI- and IoT-assisted education systems.
Table 1. AI and IoT for Smart Education.
Feature Key Benefits Technologies Used Impact on Teachers Impact on Students
Personalized Learning Tailored curriculum and lesson plans for individual students based on their learning styles and abilities. Machine learning, natural language processing, cognitive computing. Increased efficiency and effectiveness in teaching. Increased engagement and motivation for learning, improved academic performance.
Intelligent Tutoring Systems Real-time feedback and guidance for students as they work through problem-solving tasks and assessments. Artificial intelligence, natural language processing, computer vision. Reduced workload for teachers, increased ability to monitor student progress. Increased self-directed learning, improved problem-solving skills.
Virtual and Augmented Reality Immersive and interactive learning experiences for students, allowing them to visualize and explore complex concepts. Virtual reality, augmented reality, computer vision. Increased ability to deliver engaging and interactive lessons. Increased engagement and motivation for learning, improved understanding of complex concepts.
Smart Classrooms Automated and connected classrooms, with smart devices and sensors for monitoring student engagement and progress. Internet of Things, sensors, cloud computing. Increased ability to monitor and analyze student data, improved ability to make data-driven decisions. Increased engagement and motivation for learning, improved ability to collaborate and communicate with classmates.
Adaptive Learning Platforms Platforms that adapt to the learning pace and style of individual students, providing personalized feedback and support. Machine learning, natural language processing, big data. Increased efficiency and effectiveness in teaching, improved ability to monitor student progress. Increased engagement and motivation for learning, improved academic performance.
Feature Key benefits Technologies used Impact on teachers Impact on students

3. Artificial Intelligence and Internet of Things Roles at the Application and Infrastructure Levels

In this section, the focus will be on the AI and IoT roles at the application and infrastructure levels with respect to smart cities’ educational systems. As shown in Figure 1, AI can be used for personalized learning, adaptive testing, and intelligent tutoring systems at the application level. For example, an AI-powered system can analyze student data to identify areas of weakness and then provide customized learning content to help students improve [16]. Devices of the IoT, including tablets and smartboards, can also be utilized to enhance the experience of the classroom, providing students with collaborative, multimedia-rich content and allowing teachers to easily assess student understanding [17]. While at the infrastructure level, AI and the IoT can be used to improve the management and maintenance of school buildings and grounds. For example, IoT sensors can be used to monitor the energy consumption of school buildings, allowing administrators to identify areas where energy efficiency can be improved [18]. AI-powered systems can also be used to predict and prevent equipment failures, reducing downtime and maintenance costs. AI and the IoT can influence smart cities’ education systems, providing students with more personalized and effective learning experiences and making it easier for administrators to manage and maintain the school infrastructure in a smart city context [19]. Figure 41 illustrates AI and the IoT for the education systems in smart cities at the application and infrastructure levels [16]. The integration of artificial intelligence (AI) and Internet of Things (IoT) technologies in education systems brings significant benefits to smart cities by improving both the application and infrastructure levels, resulting in a more efficient and effective learning experience for students.
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Figure 1. AI and IoT for the education systems in smart cities at the application and infrastructure levels.
AI and the IoT play a vital role in optimizing and automating the education system at the application and infrastructure levels in smart cities. Home health monitoring and remote personalized learning are two roles of AI and the IoT that can be applied in smart cities’ sustainable education systems at the application level. IoT devices, such as laptops, tablets, and smartphones, provide remote learning and communication between students, teachers, and administrators. Moreover, machine learning algorithms are utilized to analyze data on student work and tailor instruction to individual student’s needs. For example, an AI system may be able to identify patterns in a student’s performance data, such as areas where the student struggles or excels, and adjust the instruction accordingly. Another approach is to use natural language processing to provide personalized feedback to students on their written work. Additionally, AI can be used to personalize learning through the application of adaptive learning systems, which calibrate the pace and challenge of instruction depending on how a student performs [20].
Moreover, AI-powered intelligent tutoring systems can be used to provide individualized instruction to students depending on their learning demands, skills, emotions, and aptitude. AI can also be used to create immersive and interactive virtual and augmented reality experiences for students in smart classrooms to enhance the learning experience. Intelligent tutoring systems (ITSs) typically consist of a student model, which keeps track of the student’s knowledge, skills, and progress, and an instructional model, which determines the appropriate content and teaching strategies to use. Some ITSs also include a dialogue module that allows students to interact with the system using natural language, which can make the instruction more engaging and personalized [21]. The IoT has been found to be effective in improving student learning outcomes, particularly in areas, such as math, science, and language learning. However, it is important to note that ITSs alone cannot replace human teachers, and it is always recommended to supplement human instruction [22].
Likewise, AI algorithms can be used to create adaptive tests that adjust to the student’s performance level, providing a clearer assessment of their knowledge and skills. Adaptive testing is a method of assessment in which the difficulty of the test questions is adjusted based on the student’s performance. By using AI algorithms, adaptive tests can be tailored to the individual student’s knowledge, skill level, and learning style. One common approach to creating adaptive tests using AI is using machine learning algorithms to analyze student performance data and determine the appropriate difficulty level for the next test question. For example, if a pupil responds to a question properly, it is followed by a more difficult question, while if they answer incorrectly, the next question will be easier. Another approach is to use natural language processing to understand the student’s response and adjust the question difficulty accordingly [23]. AI-powered adaptive tests can be used in both formative and summative assessment scenarios, providing instant feedback and identifying the student’s strengths and weaknesses. Additionally, adaptive testing can also help reduce test anxiety and increase the engagement of students. AI is also utilized in automatically grading assignments, quizzes, and exams, reducing the workload of teachers and allowing them to focus more on instruction and mentoring [24]. Table 2 demonstrates the summarized insights into how AI and IoT play a significant role at the application and infrastructure levels to strengthen the education system.
Table 2. Demonstrates the summarized insights into how AI and IoT play a significant role at the application and infrastructure levels to strengthen the education system.
Application Infrastructure Role of AI Role of IoT
Remote Learning AI algorithms can be used to personalize and optimize remote learning experiences, such as adaptive learning systems and intelligent tutoring systems, to improve student engagement and performance. IoT devices can be used to provide access to remote learning resources, such as online libraries and educational apps, and to monitor student participation and progress.
Classroom Management AI algorithms can be used to monitor and manage student behavior in real time, providing feedback and support to teachers to help maintain classroom discipline and student engagement. IoT devices can be used to monitor classroom conditions, such as temperature and air quality, and to provide data-driven insights that can be used to improve the learning environment.
Student Health and Safety AI algorithms can be used to monitor student health and safety, such as identifying symptoms of illness, tracking potential exposure to COVID-19, and providing early warning of potential health risks. IoT devices can be used to monitor student health and safety, such as tracking movement and interactions with others, and to provide data-driven insights that can be used to improve safety protocols.
Campus Management AI algorithms can be used to optimize campus operations, such as scheduling and resource allocation, to ensure efficient use of resources and reduce costs. IoT devices can be used to monitor and control access to campus facilities, such as classrooms and labs, and to provide data-driven insights that can be used to improve campus safety and security.
Parent–Teacher Communication AI algorithms can be used to facilitate communication between parents and teachers, such as chatbots and virtual assistants, to improve parent engagement and support student learning. IoT devices can be used to provide real-time updates on student progress and activities, such as homework completion and attendance, and to facilitate communication between parents and teachers.
Learning Analytics AI algorithms can be used to analyze data on student performance and behavior, providing insights that can be used to improve teaching and learning strategies. IoT devices can be used to collect data on student behavior and engagement, such as tracking student interactions with learning resources and identifying patterns in student participation.
At the infrastructure level, AI and the IoT also play a significant role. For example, in a smart classroom environment, IoT sensors can be used to monitor and control lighting, temperature, and other environmental factors in classrooms to optimize the learning environment. In attendance tracking, IoT devices, such as RFID or NFC tags, can be used to track student attendance and location, helping to improve the safety and security of the students and school staff. In smart cities, students also benefit from AI- and IoT-assisted smart libraries and labs, which enhance the services and resources available in libraries and research labs. IoT devices can be utilized to track the usage of books and other library resources, helping to optimize inventory and reduce costs [25].
AI can also be used to improve the search and discovery of resources, such as books, articles, and multimedia. AI-powered search algorithms and robots enhance the context and intent of a user’s search query and return more relevant results. AI analyzes library usage data and provides personalized recommendations to users [25]. In research labs, AI can be used to assist with data analysis, experimentation, and modeling. In this case, AI algorithms analyze large data sets, identify patterns and correlations, and make predictions. Additionally, AI can be used to optimize and automate laboratory processes, such as sample preparation, analysis, and data collection. Smart libraries and labs can also be used to improve accessibility, security, and energy efficiency [26]. Therefore, AI and the IoT at the application and infrastructure levels in the education systems of smart cities can help to automate and optimize various systems and processes, resulting in an intelligent campus where IoT devices are employed to track students’ and teachers’ movements on campus, to improve security, and to optimize the usage of the infrastructure as well as improved efficiency, productivity, and cost savings, and an enhanced quality of education for students [27].

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