Importance & applications of IoT in Education

Smart school/ campus developments

The use and development of IoT for the smart classroom are essential in monitoring and measuring students' performance and efficiency. The monitoring factor considers critical factors, including air quality, temperature, and humidity, which can help measure the effectiveness of the classroom environment (Abbasy & Quesada, 2017). According to Kiryakova et al. (2017), IoT monitors classes, boosts creativity, addresses administrative activities, and promotes an interactive environment. The development of an intelligent classroom environment, in that case, depends on the application of respective factors to identify the monitoring measures and their impacts.

A new environment for knowledge acquisition

According to Chauhan et al. (2019), developing a new environment goes into class management, with access to authentication and electronic devices essential. The class management focuses on new monitoring strategies for the students. Creating a new e-learning platform and center is another factor to consider in the analysis. The new environment considers monitoring the environment, class attendance, engagements, and coordination, all of which promote the e-learning factor (Soni, 2019). According to Ionescu-Feleaga et al. (2021), the development of the IoT technologies acceptance models considers usefulness, perceptions, intentions, facilitation, and training, all of which can determine knowledge acquisition.

School operation effectiveness

The operationalization of the school through IoT can consider the education business model as identified by Bagheri & Movahed (2017). In the model, some factors to consider are access control in the classroom, improving learning and teaching, monitoring students' health, and energy management. Kumar et al. (2021) identify the application of IoT in then operations, including designing ubiquitous classrooms, intelligent learning environments, and services computing systems. According to Pai (2017), the smart classroom leads to a better learning experience, reduced costs, improved operational efficiency, safety improvement, and reliability, promoting operational efficiency.

Monitoring students and Tracking behavior for real-time performances

IoT's monitoring and tracking capabilities can embrace real-time data collection, measurement, and decision-making. According to Gul (2017), smart classroom management utilizes interactive whiteboards, attendance-tracking systems, security cameras, and mobile devices, which can offer real-time metrics. In the industrial engineering setup, the primary issues come in laboratory utilization, with the IoT offering a monitoring and tracking structure for the students (Zorc, 2017). The administrative and monitoring factors remain at the core of ensuring that the performance metrics are standardized to create a stable evaluation technique.

Sensor-driven Decision-making analytics

The sensor-driven environment is part of the critical uses of IoT, with the machines expected to be sources of information and decisions (Al_Janabi, 2020). By designing an integrated system that can collect data in real time, classroom administrators can make decisions to fit classroom needs. According to Bakla (2018), IoT in learning processes utilizes the data management layer to identify the interests, preferences, achievements, and scores, which can derive the decisions required. Another approach focuses on the framework implementation, which helps set the classroom based on the needs and use concepts such as FPGA (Magyari & Chen, 2021).

Personalized and adaptive education

According to Banica et al. (2020), access to personalized content and learning activities that conform to individual needs benefits the IoT as an educational tool for students. Some of the concepts that come up from the IoT application include smart teaching, which creates a variety of choices for the learners (Pai, 2017). The adaptive factor captures intelligent technologies that can deal with learning analytics to promote personalized education needs. Therefore, the smart learning concept remains integral in addressing the learning requirements.

School environment monitoring through real-time interactions

The school environment plays a core role in guiding the learning process. Identifying the classroom environment factors such as humidity, temperature and airflow are sensory attributes designed and developed from the IoT (Bajracharya et al., 2018). Such factors can help assess the suitability of the environment based on educational needs. According to Dai et al. (2021), IoT creates a smart environment with predefined conditions and metrics for performance measurement and improvement. The aim is to condition the students to learn in the best environment possible while identifying and dealing with the school environment's challenges.

Collaboration among educators and learners

The collaboration between educators and learners emanates from analyzing the critical factors that promote class interactions for learning purposes. According to Gómez et al. (2013), the interactions between the educators and learners are a factor of teaching processes and the real-time metrics within the systems. Improving the collaboration in the learning process also captures the use of robotics since they provide the physical aspects required in the learning process. IoT in learning encourages robotics to engage and make real-time decisions, which is crucial in promoting collaborations (Romeo et al., 2020).

Students learn at their own pace and enhance distance learning.

The convenience factor is part of the benefits of IoT. IoT in distance education has been substantial, with the use of GPRS and ZigBee being some of the network development systems enabling learning (Ramlowat & Pattanayak, 2019). By ensuring that the system is self-monitoring, the tracking and monitoring processes are based on the teacher and learner inputs. Such factors lead to learning structures and management that appreciate the students and their needs (Rukmana & Mulyanti, 2020). By use of wireless networks, students can access the learning process away from the physical classroom, which promotes time and cost conveniences while ensuring distance learning (Chweya & Ibrahim, 2021)

Improves the effectiveness of theoretical teaching

IoT in instructional design is an essential factor in assessing the changes in the structure while integrating spatial, temporal, and persistence information, which can promote the appreciation of theories (Charmonman et al., 2015). The development of the IoT-based education model focuses on the teaching-learning processes, which facilitate learning effectiveness (Ramlowat & Pattanayak, 2019). According to Du et al. (2021), closing the gap between theoretical approaches and practical skills remains part of the goals of IoT in higher education. With some of the courses requiring a connection between the theories and practical aspects, IoT creates an environment that promotes virtual reality.

Challenges facing IoT in the Education

Cost of installation, training, power, and internet

IoT comes with installation requirements, with the cost factor being important. In a study by Chweya & Ibrahim (2021), a cheaper education approach is essential in promoting effectiveness and reliability in the system. With most learning systems focusing on infrastructure that derives the quality of education, developing an intelligent learning environment remains a challenge for most schools. According to Abbasy & Quesada (2017), developing the systems is costly, despite the increased use of the internet and virtual learning environments. The cost factor comes in the IoT systems, the expertise, and the sustainability factors, which can increase the cost of the IoT education system.

Cyber security risks require more layers of security which is expensive.

IoT development comes with several layers, with the security factors being a challenge. Personal responsibility and the lack of devices updates are among the factors leading to increased risks (Tawalbeh et al., 2020). Automation remains essential in ensuring that IoT attains the expected goals, with the challenges emanating from the vulnerability in the systems. According to Tomás & Teixeira (2020), vulnerability exposes the systems to piracy, errors, and hacking, affecting the IoT networks. The security layers come at a cost, affecting the sustainability of these systems in the learning environment.

Privacy attacks

Privacy is part of the data security requirements. According to Tawalbeh et al. (2020), privacy factors emanate from the omnipresent intelligence used in the IoT systems, which affects the ability to oversee privacy rights. Internet networks are also an issue, which affects the ability to protect personal information. He et al. (2021) identified the access control challenge as the significant factor affecting the accessibility and privacy of users. The use of blockchain and cyber security systems remains a solution, despite the increased challenges emanating from new cyber-attacks in the IoT systems He et al. (2021).

Lack of generic frameworks

Even with the benefits, the frameworks are critical in ensuring that IoT fits into the education systems. According to (Zorc 2017), the IoT technologies are still in their infancy stage, with the development of framework lacking the standardization requirements. The issue influences the network traffic, security, storage, and technological requirements. Building a framework that meets the learning requirements and deals with security issues is a challenge for learning institutions (Enterprise, 2020). Creating models that include analytics, adaptive teaching, collaborative learning, automated systems, and intelligent learning requires education models to develop and sustain these systems (Banica et al., 2020).

Incompatibility of some IoT devices

Their role and utilization influence the development of IoT devices in the smart environment. The incompatibility factor comes from the differences in the systems, with the use of heterogeneous technologies and unrelated technologies being part of the compatibility factors (Mathews & Gondkar, 2017). The incompatibility goes into the development of the smart classroom, whereby the devices used and structures should align with the IoT systems in place (Banica et al., 2020). The transitions within the systems come from the changes in the IoT infrastructure, creating the need for new compatibility features.

Lack of acceptability and stakeholders' goodwill to adopt new technology

The acceptability issue determines how the IoT technologies are utilized and the role of stakeholders in ensuring that the technologies favor the existing stakeholders. Students and education stakeholders may look into the high cost of installation, lack of devices, and the IoT shifts as part of the challenges (Ionescu-Feleaga et al., 2021). The other factor to consider is the institution-related factors that create the norms and policies to influence the education system. Stakeholders react differently to the new technologies depending on the policies and existing infrastructure (Butt et al., 2020). The goodwill comes from appreciating the benefits while looking into the costs of existing alternatives.

Lack of scalability

Scalability is an essential structure in evaluating the functionality of IoT systems. Kassab et al. (2018) identify the scalability concerns as critical in collecting and utilizing big data. Access to systems that can tackle big data is a consistent challenge for an intelligent education environment while promoting the quality of the learning system. Since the IoT technologies are still developing, the infrastructure factor remains a determinant of the existing systems (McRae et al., 2018). The diverse learning needs across the education system create a consistent problem in managing the IoT while focusing on scalable solutions.

Lack of ICT skills among students

ICT skills are vital in achieving the ICT requirements and skills in IoT implementation. According to Du et al. (2021), lack of skills remains a current and future challenge for IoT implementations in schools. The advancements in the IoT and the demands from the students are among the influencing factors. Despite the increased use of the internet and related devices, some students lack the expected skills in utilizing the IoT, making the global use of IoT a challenge (Bakla, 2018). The gap reduces the willingness to adapt to the new technologies, despite their potential benefits in the learning process and environment.

Lack of expertise

The expertise factor relates to the individual capabilities to utilize the IoT systems and the related ICT components. The teacher-related factors are integral in evaluating the expertise, with the gaps between the theories and the practical skills being part of issues affecting IoT in education (Butt et al., 2020). The application of IoT in STEM education is challenging due to virtual reliability concepts that many not materialize in the real world (McRae et al., 2018). The creation of expertise for the instructors and students is a training perspective that may require countries to develop new curricular

Potentials of IoT in education

Improve student performance while working within the intelligent classroom 

Students' performance is part of the determinants of the reliability and effectiveness of the existing education systems. According to Ionescu-Feleaga et al. (2021), the smart classroom offers improved performance based on the communication strategies that promote the education system and its achievements. The students and instructors can encourage interests and overcome challenges affecting individual performance. The other potential is improving the teaching and learning, which comes from increasing the role of the intelligent classroom in enhancing the student's learning requirements (Bagheri & Movahed, 2017). The instructors can influence performance by setting standards that trigger optimal learning processes through the IoT systems. 

Transform the education sector in terms of engagements, productivity, and effectiveness

According to Charmonman et al. (2015), the potential of IoT goes into connecting students and teachers, streamlining administration, and integrating the students' unique needs. The potential comes from creating a regulated classroom, which enables the instructors to influence the students and their activities in the school. The other factor to consider is creating a virtual environment, which is easily manageable. According to Soni (2019), effective management of the education system makes room for improved productivity. Productivity measures the quality of education and the skills gained, which are integral in assessing the education systems. 

Reduce the costs of education management 

The other potential of the IoT is cost-effectiveness and management, with the expectation of deriving the education management criteria that use pre-controlled systems. According to Bagheri & Movahed (2017), developing the campus energy management system and monitoring the ecosystem is essential for cost management. By reducing the need for physical classrooms or adjustments to fit student needs, the potential to reduce the costs of administrating education policies is high (Zorc, 2017). The main issues to focus on are the acceptance and the training needs, which can be accommodated in the current education systems to reduce the existing gaps (Pai, 2017). 

Promote the interactions between the instructors and students in the intelligent classroom

Interactions between students and instructors create a constructive relationship with the students. IoT is a source of convenience since the parties can engage, regardless of the barriers. Cloud-based virtual interaction is an essential source of interactive environment, with the record system guiding the instructor-student strategies (Chauhan et al., 2019). According to Bagheri & Movahed (2017), the interactive nature of IoT technologies goes a long way to developing a system that can actualize the engagements and improve constructive communication in the class. The IoT tools used in the smart classroom enable these interactions. 

Providing a support system for the education system and covering gaps in the classroom 

While the education systems are developed to attain definite goals, access to the support systems remains vital. Gómez et al. (2013) propose the mandates of the IoT networks in supporting the education systems by offering a consistent and reliable system for connecting students and instructors. The other support structures provide an enabling environment, which enables monitoring of students, the class, and the performances. According to Mathews & Gondkar (2017), IoT technologies are essential sources of control, tracking, and surveillance to enable optimal results from the education systems. 

Increasing virtual and distance education as part of reducing barriers to education

IoT in distance education is a systematic factor that can be improved and implemented by sustaining the environment to promote engagements through virtual systems. Ramlowat & Pattanayak (2019) engage technologies such as experiment terminal groups (ETG) and GPRS to improve the development of virtual environments. Developing a virtual environment is a significant trend, with IoT promoting the role of critical environments in connecting the global classroom (Butt et al., 2020). The potential to eliminate physical barriers considers theoretical applications' implications, especially in engineering courses. IoT technologies encourage practical skills through robotics (Shao et al., 2021). 

Offering a learning-friendly environment, based on the development of factors that reduce inconveniences 

The creation of a learning-friendly environment has become part of the concerns for the education systems. IoT provides an intelligent climate with regulations on the temperature, humidity, and airflow, influencing the concentration (Abbasy & Quesada, 2017). Creating a learning management system that can improve the systems and encourage conveniences for students is an essential strategy for organizations. In Rukmana & Mulyanti (2020), identifying the learning management requirements would be necessary for establishing improved management of the learning systems. The environmental factors should consider the decision-making criteria and create an improvement strategy to sustain the learning management system. 

Green technologies and their role in sustainable education models and systems

The sustainability factor is integral in the creation of the IoT education systems. The potential of green IoT goes into developing optimal resource utilization, reuse, and recycling and promoting awareness (Ramlowat & Pattanayak, 2019). Such factors would encourage the role of education in promoting sustainability and green technologies. The sustainability factor also looks into the data security, privacy, and access control factors that have affected ICT development in the education system. According to Tawalbeh et al. (2020), the potential for improving the reliability of IoT in education considers the sustainability of access control through increased investments in security and privacy factors. 

Future of IoT in Snart Education

It will build more brilliant schools to provide efficient and practical accessibility.

The primary factor and approach used in IoT are developing an intelligent environment for students to learn. The future looks into influencing student performance through identifying the individual needs and addressing the specific classroom needs (Charmonman et al., 2015). The inclusion of technologies such as cloud storage would be essential milestones in promoting the data storage, analysis, and boosting the effectiveness of smart classrooms. According to Kumar et al. (2021), incorporating a cloud-based smart classroom would tackle the data and information requirements.

It will help create an adequate ground for combining online and offline teaching forms.

The prevalence of offline classrooms cannot be overlooked when developing smart classrooms and utilizing IoT systems. According to Mathews & Gondkar (2017), IoT can provide the support structures required to promote technologies in the school. Developing an integrated approach that combines online and offline techniques can effectively enable the education system models. The increased use of IoT skills at home is one of the culturally-instigated impacts of teaching from the IoT-based classroom (Van der Zeeuw et al., 2020).

It will create adaptive brilliant students' assessments systems.

The creation of the student assessment systems through technological application is a rising agenda in the education system. The adaptive factors in the IoT come from facilitation that crates better management of the systems while encouraging the insights from the learners and the students (Soni, 2019). Some of the works in the adaptive environment include the use of botnet detection as part of ensuring that the assessments of the education systems consider all factors, including the access control factors (Shao et al., 2021). Even with the challenges of record systems in the current systems, improving the cloud systems for IoT remains a future for IoT in intelligent education.

It will satisfy the demands and needs of the student and educator community in a larger context.

The demand from the student and educators can determine the development of a compatible learning management system. According to Rodney (2020), the development of IoT in intelligent education can promote satisfaction amongst students and educators. The benefits come in creating a facilitation strategy that can guide the students and educators in developing effective systems. In Chweya & Ibrahim (2021), the transition from the traditional learning models captures the need to personalize the education systems to meet the learner and educator needs. These needs can be influenced by the development of a regulated learning environment.

It will enhance IoT-based learning frameworks that can create a new learning paradigm.

The new learning paradigm comes with intelligent systems, which connect the education, teaching, and learning processes. The development of innovative education, smart teaching, and intelligent learning are future strategies that could influence the achievements made in the innovative education system (Pai 2017). According to Rodney (2020), the IoT education system uses hierarchy, homeostasis, and purposiveness to influence the learning paradigm. Such factors will redefine the existing learning systems to ensure that the learning environment band system aligns with the technological advancements.

It will minimize the cost of operations, lowering time wastage, and bring comfort to learners and educators.

By developing a system that can monitor the existing environment and learning management system, IoT has the opportunity to reduce costs of operation, time wastage and promote comfort. According to Du et al. (2021), the cost factor remains a challenge due to the gaps in infrastructural development. However, the future may see improved results due to the reduced maintenance costs and the development of skills that promote the efficiency of IoT in the education systems. The achievement of sustainable and intelligent learning systems can automate systems, which leads to better management of the system process (Riekki & Mammela, 2021).

It will open educational spaces for new teacher-student interactions and student-machine-material interactions.

Developing an interactive environment is part of the research approaches in using IoT in education. The study into the gaps in IoT application in education systems reveals the need for dedicated efforts towards promoting communication, with IoT offering machine networking systems (Ionescu-Feleaga et al., 2021). By integrating blockchain technologies in IoT, the future sees the ability to capitalize on big data systems. According to He et al. (2021), the big data factor is part of the developments that can influence the achievements made concerning interactions and their positive impacts in the smart classes.

It will streamline operations such as attendance, fee alerts, and student reports.

The organizational factors in a classroom can be automated to promote reliability and reduce human errors in the systems. According to Kumar et al. (2021), IoT can create an automatic attendance system with face recognition and user guidance applications to provide information. Such investments are integral in influencing the operations within the classrooms. The other consideration is the role of IoT in promoting communication and real-time metrics (Ionescu-Feleaga et al., 2021). These metrics can offer the assessment criteria to create better operations management while addressing the upcoming issues affecting the students and the learning processes.

It will eradicate all barriers to education related to physical location, language, and economics.

One of the contemporary issues in the education systems is promoting globalization and eliminating the barriers affecting education, language, and economics. According to Butt et al. (2020), information systems present global education system opportunities. The ICT role in IoT is integral, making the future of IoT align with the globalization strategy. IoT applications will also remove physical barriers in education (Paganelli et al., 2020).

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