Need a perfect paper? Place your first order and save 5% with this code:   SAVE5NOW

Impacts of Wearables and Internet of Things (IoT) Technologies on Training and Development

The advancements in technology inspire organizations to upgrade their training and development content in the current digital and fast-paced world. Technology such as wearables, AI, and IoT have largely altered the learning and development experience for individuals, in various spheres. Imagine a future where learning becomes interwoven within our daily activities, feedback happens promptly and the inputs that are tailored to the individual allow for rapid growth. AI/IoT and wearables have an impact on the training and development phases, as suggested by the article. This research looks at the origins, collective benefits, disadvantages, prospects for application through a range of sector-wise deployment, and the potential effect on the trainers and designers to highlight the exigency of the technologies for learning.

Wearables

Wearable technology can be traced back to the late 1960s and early 1970s when Edward Thorp and Claude Shannon invented a tiny computer that easily fitted into a shoe. This can be considered a pioneer stage of wearable technology, as it showed how people have worked to integrate computing power into the tiny and wearable form factor. While the decades have passed, microelectronics and sensor technologies have helped wearables become very tiny, but powerful and versatile devices. To provide more tailored and captivating user experiences, wearables have come from blood pressure monitors to smartwatches and augmented reality glasses. Wearables consist of different sensor modules, processors, and connection devices that are worn on the human body. One of the main functions of wearable devices is communication, navigation, health and fitness monitoring, and productivity improvement. Smart watches take over a person’s heart rate, exercise, and calls and texts, while smart glasses provide hands-free data and augmented reality.

Advantages

Enhanced Accessibility:

Wearable technology gives fast and instant access to pieces of information and solutions. Wearables, unlike computers and mobile phones, are worn directly on the body, hence they don’t need to be in pockets or bags, conveniently available all the time (Dian et al., 2020). These users’ access to health data monitoring, communication, and important information is uninterrupted.

Real-Time Feedback:

In wearable technology, instant feedback represents another advantage. Wearables report heart rate, sleep quality, and daily physical activities by analyzing the sensor data in real time. Immediate feedback realizes more educated health, productivity, and well-being choices through which the habits and activities of users can be steered.

Disadvantages

Privacy Concerns:

The widespread use of wearables has introduced the privacy problem of accumulating, storing, and transferring data. Wearables collect vital information about health, location, and behavior, which could be copied, compromised, or misused. Wearables when integrated into internet platforms and services may place users at risk of receiving targeted ads, data profiling, and privacy invasion.

Limited Screen Size and Interface:

Wearables have smaller screens and interfaces even though they are portable. Usability and usefulness may be limited, making it hard to use complicated apps and materials. The compactness of wearables may limit their efficiency in showing information and interactions resulting in their poor utility in particular situations.

Future Use in the Healthcare Industry

Remote Patient Monitoring:

The wearable technology brings about a revolution in healthcare through remote patient monitoring, which in turn allows vital signs to be monitored in real-time, and medication adherence and activity monitoring. By adopting such a personalized approach we can improve chronic disease management, post-surgical recovery, and overall patient outcomes.

Personalized Health Coaching:

Wearables act as personal health coaches, giving feedback and customized recommendations considering health goals and testimonials. The examination of sensor data assists in finding repetitions, trends, and improvements hence developing the player’s drive and responsibility.

Implications for Trainers and Designers

Need for Tailored Content Delivery:

The integration of wearable tech- in training programs demands modifying the method of content delivery to the attributes of devices by breaking content up into small modules, optimizing for mini-screens, and involving voice and gesture controls.

Integration of Wearable Data into Training Programs:

Instructors and trainers could create learning plans to translate gathered values of wearables to look at learners’ habits, performances, and the areas where improvement is essential. Wearable information, in turn, augments the learning speed, efficacy, and learner comfort, providing an integrated learning experience.

Artificial Intelligence / Internet of Things (IoT)

Development and Evolution:

The Internet of Things (IoT) emerged with everyday objects connected to the internet, birthing smart homes. John Romkey’s 1990 creation of an IoT toaster marked its beginnings. IoT’s growth, fueled by wireless communication, sensors, and cloud computing, has transformed industries like healthcare and transportation. In training, AI and IoT enable personalized learning through real-time adjustments to programs based on IoT data analysis (Sharma et al., 2019). Virtual assistants enhance conventional training methods, fostering engagement and retention.

Advantages

  1. Adaptive Learning Experiences:

AI and IoT contribute to evolutionary learning, where learning items are either made simpler or more complex based on the learner’s level and progression in real-time. The application of a tailored approach leads to more engagement and the acquisition of a stronger understanding of the material charted according to their learning styles.

  1. Data-Driven Insights:

AI and IoT can provide trainers with valuable data-driven features about learners’ competence levels and choices. Software and AI improve programs, evaluate efficiency, and so do connected sensors delivering feedback instantaneously from which increases may be made to the quality of the content and delivery (Pinon et al., 2019).

Disadvantages

  1. Dependency on Data Accuracy:

The training success of data-based AI and IoT is inextricably linked to the quality and reliability of IoT data. Not having accurate data could immensely affect the insights and recommendations, thus, the efficacy of learning quality is likely to diminish. In addition to that, there can be issues of data sources biasing or algorithms making unfair decisions that would hurt or undermine some learners.

  1. Ethical Concerns and Bias:

AI-IoT combination, bringing with it privacy, security of data, and bias of algorithms, may highlight the privacy issues witnessed as personal data management, transparency, and discrimination leading to education and training.

Future Use in Manufacturing Industry

  1. Predictive Maintenance:

In manufacturing, AI and IoT make predictive maintenance systems that forecast equipment failures possible. AI algorithms can identify anomalies, predict issues, and prevent equipment breakdown by processing IoT sensor information on machines. This proactive approach reduces downtime, maintenance costs, and production waste.

  1. Augmented Reality Training:

AI and IoT enable AR training solutions in manufacturing, where AR wearables with IoT sensors provide hands-on training, increasing learning retention, work performance, and safety.

Implications for Trainers and Designers

  1. Shift in Role towards Curating Content:

AI and IoT in training require trainers and instructional designers to assume the role of content curators instead of content creators. Trainers need AI to examine student data, look for the appropriate resources, and design learning routes for each student. It is also important for teachers to choose and configure IoT devices for effective data usage purposes in instructional design.

  1. Emphasis on Data Literacy and Ethical AI Use:

The trainers and designers must cognize data proficiency and ethics in AI and IoT. They must be proficient in interpreting and critically evaluating data, spot ethical dilemmas and biases, and adhere to data privacy regulations. Trainers also encourage fair AI utilization by mandating transparency, accountability, and data care in the training programs.

References

Dian, F. J., Vahidnia, R., & Rahmati, A. (2020). Wearables and the Internet of Things (IoT), applications, opportunities, and challenges: A Survey. IEEE Access8, 69200-69211.https://doi.org/10.1109/access.2020.2986329

Sharma, N., Madhavi Shamkuwar, & Singh, I. (2018). The History, Present and Future with IoT. Intelligent Systems Reference Library, 27–51. https://doi.org/10.1007/978-3-030-04203-5_3

Pinon, M. M. B., Nascimento, M. H., de AB Junior, J., Tavares, T. F. D., & de Souza Silva, V. L. (2018). Applications and Advantages of the Internet of Things (IoT) at Industry (189-194). ITEGAM-JETIA4(15), 189-194.https://www.researchgate.net/publication/327927138_Applications_and_Advantages_of_the_Internet_of_Things_IoT_at_Industry_40

 

Don't have time to write this essay on your own?
Use our essay writing service and save your time. We guarantee high quality, on-time delivery and 100% confidentiality. All our papers are written from scratch according to your instructions and are plagiarism free.
Place an order

Cite This Work

To export a reference to this article please select a referencing style below:

APA
MLA
Harvard
Vancouver
Chicago
ASA
IEEE
AMA
Copy to clipboard
Copy to clipboard
Copy to clipboard
Copy to clipboard
Copy to clipboard
Copy to clipboard
Copy to clipboard
Copy to clipboard
Need a plagiarism free essay written by an educator?
Order it today

Popular Essay Topics