IOT-Driven Robots: Revolutionizing Automation

IOT-Driven Robots: Revolutionizing Automation

Pradnya Bhoye, Vishwakarma Institute of Technology

Pune, Maharashtra, India.

Monali Bhujbal Vishwakarma Institute of Technology

Pune, Maharashtra, India.

Abhijeet Budhwant Vishwakarma Institute of Technology

Pune, Maharashtra, India.

Abstract:

The convergence of the Internet of Things (IoT) and robotics has led to transformative innovations across multiple sectors, promoting advancements in automation, real-time data processing, and autonomous decision-making. This paper reviews the recent developments in IoT-driven robotics, highlighting its applications in industrial automation, healthcare, agriculture, and environmental management. Key areas of focus include the role of cognitive robotics in enhancing sustainable waste disposal, the integration of IoT-enabled safety protocols in industrial environments, and machine learning techniques for improved network security within IoT ecosystems. Additionally, the paper addresses ethical considerations, particularly related to job displacement and data privacy, as IoT and AI-driven robotics become increasingly prevalent. This synthesis of literature underscores the transformative impact of IoT-aided robotics on societal infrastructure and lays the foundation for future research to optimize human-robot interaction, scalability, and resilience.

Keywords-IoT, Robotics, IoRT (Internet of Robotic Things), AI- IoT (Artificial Intelligence-Internet of ThingsIoT-driven robotics, industrial automation, healthcare, precision agriculture, cognitive robotics, machine learning, network security, sustainability, ethical considerations, autonomous systems, human-robot interaction, smart cities, collaborative robots, real-time data processing

INTRODUCTION:

The rapid advancement of Internet of Things (IoT) technology, combined with the innovations in robotics, has initiated a paradigm shift across various industries, driving significant improvements in automation, precision, and efficiency. IoT- driven robotics leverages interconnected sensors, actuators, and devices that enable robots to interact with their surroundings, process vast amounts of data, and make autonomous decisions in real-time. This fusion of IoT and robotics has paved the way for Internet of Robotic Things (IoRT), a framework that empowers robots to perform complex tasks with minimal human intervention.

The convergence of IoT and robotics has wide-reaching implications in sectors such as industrial automation, healthcare, agriculture, and urban development. In manufacturing, IoT-driven robots enhance productivity through real-time process monitoring and precise quality control, addressing the growing demand for high-efficiency operations. In healthcare, the use of IoT-enabled robotics allows for remote patient monitoring, timely interventions, and even assisted surgeries, thus improving patient outcomes and optimizing resource allocation. Similarly, in agriculture, IoT-powered robots facilitate precision farming by automating labor- intensive tasks like soil monitoring, irrigation, and pest control, leading to increased crop yields and sustainable resource management.

However, alongside the promise of enhanced automation and productivity, IoT-driven robotics introduces ethical, security, and environmental considerations that require careful attention. The integration of AI and machine learning within IoT frameworks brings new challenges related to data privacy, cybersecurity, and job displacement. Furthermore, the implementation of these technologies calls for sustainable practices, especially in smart city applications where waste management and energy efficiency are crucial.

This paper explores the current advancements in IoT-driven robotics across key sectors, including industrial automation, healthcare, and agriculture, while discussing the ethical and technical challenges associated with this field. Through a comprehensive review of recent literature, we aim to highlight the transformative impact of IoT-driven robotics on modern industries and the considerations necessary for responsible and sustainable adoption.

Literature Survey:

The convergence of the Internet of Things (IoT) and robotics has garnered significant attention in recent years, spurring numerous studies and technological advancements across multiple sectors. This literature survey explores key research findings and developments in IoT-driven robotics, focusing on industrial automation, healthcare, agriculture, and ethical concerns.

(below reference)

Investigate the role of circular economy principles combined with Industry 4.0 technologies like IoT and AI to enhance sustainable healthcare waste disposal in smart cities. Similarly, Javaid et al. (2021) emphasize the potential of cognitive robotics in automating waste management, leveraging AI and machine learning to optimize disposal processes. Both studies highlight how advanced technologies contribute to sustainable waste management in smart city environments Chauhan et al. (2021) [1].

Conduct a systematic literature review on safety and ergonomics in the field of industrial collaborative robotics, highlighting emerging research areas. The study focuses on the integration of robotics in manufacturing environments, emphasizing the need for enhanced safety protocols and ergonomic designs. By analyzing recent advancements, the authors identify key challenges and propose strategies to improve human-robot interactions, aiming to optimize both worker safety and productivity. This research underscores the importance of addressing ergonomic and safety concerns as collaborative robotics continues to grow in industrial applications Gualtieri et al. (2021) [2].

present a machine learning approach utilizing artificial neural networks to detect malicious nodes within IoT networks. This study, featured at the International Conference on Machine Learning, IoT, and Big Data, highlights the application of neural networks in enhancing network security by accurately identifying and mitigating potential threats. The authors emphasize the effectiveness of AI-driven techniques in strengthening IoT infrastructures against malicious activity, thereby contributing to more secure and resilient IoT networks. This research illustrates the crucial role of machine learning in advancing cybersecurity within IoT ecosystems Liyakat et al. (2023) [3].

A machine learning and IoT-based approach for detecting student health conditions. Presented at the IEEE MysuruCon, this study integrates IoT devices with machine learning algorithms to monitor and analyze students' health data, enabling early detection of potential health issues. The authors demonstrate how leveraging IoT and AI technologies can facilitate real-time health monitoring in educational settings, promoting proactive healthcare solutions. This research underscores the potential of IoT and machine learning in enhancing health detection and management within student populations Pradeepa et al. (2022) [4].

Explore various Internet of Things (IoT) applications within the agricultural sector, as detailed in Internet of Things A to Z: Technologies and Applications. The authors discuss how IoT technologies enhance agricultural practices through precision farming, real-time monitoring, and automated systems, which improve crop yields and resource efficiency. By implementing

IoT solutions, farmers can better manage resources, optimize processes, and reduce environmental impacts. This research highlights the transformative role of IoT in advancing sustainable agriculture and boosting productivity Zhang et al. (2018) [5].

Examine the role of wireless sensors and IoT in agricultural management, as detailed in the International Journal of Electrical and Computer Engineering. The authors demonstrate how IoT-enabled sensors facilitate real-time monitoring of crop and soil conditions, enhancing decision-making and resource management. By integrating wireless sensor networks, farmers can optimize irrigation, manage soil health, and increase crop productivity. This study underscores the effectiveness of IoT technologies in supporting sustainable agricultural practices and improving overall efficiency in farming operations Navulur and Prasad (2017) [6].

The design of Cyber-Physical Systems (CPS) and IoT applications for smart buildings and cities in IET Cyber- Physical Systems: Theory & Applications. The authors highlight frameworks that enhance energy efficiency, security, and user comfort by integrating IoT sensors. This study emphasizes the role of CPS and IoT in advancing sustainable urban development and improving life quality in smart cities Shih et al. (2016) [7].

Provide an overview of recent advances and future challenges in CubeSat communications in IEEE Communications Surveys & Tutorials. The authors discuss the development of CubeSat technologies, including their potential applications in satellite communications and Earth observation. They also address challenges such as limited power, bandwidth constraints, and orbital dynamics. This study emphasizes the importance of addressing these challenges to enhance the effectiveness of CubeSat communication systems and expand their role in the future of satellite communications Saeed et al. (2020)[8].

Features of IOT:

The features of the Internet of Things (IoT) are essential in advancing IoT-driven robotics, influencing how robots interact, operate, and innovate in various industries.

Fig 1: Features of IoT (source:- appinventive)

1. One of the most fundamental features of IoT is connectivity. It enables a network of devices, sensors, and systems to communicate over the internet. In robotics, this means that robots can be monitored and controlled in real time, allowing them to interact seamlessly with other machines or even humans. For instance, in smart factories, robots can communicate with conveyor belts or other equipment to ensure production runs smoothly without interruptions. Technologies like Wi-Fi, Bluetooth, and 5G facilitate these connections, creating a cohesive environment where robots and machines work together efficiently.

2. IoT-powered robots also benefit greatly from sensors and actuators. Sensors gather real-time data such as temperature, motion, or pressure, allowing robots to sense their environment and make informed decisions. Actuators perform actions like moving objects, adjusting angles, or executing specific tasks based on the data received. For example, in agriculture, robots equipped with environmental sensors can determine the right time to water crops or plant seeds based on real-time soil data. This adaptability allows them to work autonomously and optimize operations in dynamic environments.

3. A crucial aspect of IoTs impact on robotics is real-time data processing and edge computing. Robots need to process large amounts of data on the spot to react swiftly. By using edge computing, data can be processed locally, reducing latency and enabling robots to act autonomously without relying on remote cloud servers. Autonomous vehicles are a great example of this, as they use real-time processing to make split-second decisions, such as avoiding obstacles or adjusting their route based on traffic conditions. In healthcare, surgical robots rely on real- time feedback to adjust their movements during delicate operations, improving precision and patient safety.

4. The integration of autonomous decision-making in IoT allows robots to operate independently, thanks to AI and

   machine learning. These intelligent systems enable robots to analyze complex datasets, recognize patterns, and make decisions without human intervention. For example, collaborative robots (cobots) in industrial settings can learn from their environment and adapt to changes, ensuring continuous operation even in unpredictable situations. They can adjust their workflow to complement human workers, handling sophisticated tasks with minimal guidance.

5. Another feature is scalability. IoTs flexible architecture allows for the integration of more devices without performance issues. This is especially relevant for large-scale robotics applications, such as managing fleets of drones or autonomous vehicles in logistics. In warehouses, IoT systems ensure that multiple robots can operate simultaneously, coordinating with each other to transport goods efficiently. Whether its one robot or a thousand, the system can handle the load seamlessly.

6. Interoperability is another key aspect of IoT in robotics. With IoTs open infrastructure, robots from different manufacturers can communicate and work together within the same environment. In smart factories, for instance, robots from different brands collaborate on the production line, ensuring smooth operations without compatibility issues. This flexibility means that robotic systems can be easily integrated into existing infrastructure, enhancing productivity across various industries.

7. In addition to edge computing, cloud computing plays an important role in IoT-driven robotics. Cloud integration allows robots to offload data processing tasks, reducing the need for heavy local hardware. This is particularly helpful for robots engaged in data-heavy tasks, such as precision farming. Robots can access the cloud to analyze vast datasets, such as weather forecasts or soil conditions, and make more accurate decisions about when to irrigate crops or apply fertilizers. This cloud- driven approach enhances the efficiency and intelligence of robotic systems.

8. Remote monitoring and control are invaluable features that IoT brings to robotics. Robots can be controlled and monitored from faraway locations, allowing industries like agriculture, mining, or exploration to benefit from robotics even in remote areas. For example, in healthcare, IoT-enabled service robots in hospitals can be directed by doctors from different locations, assisting with patient care when human professionals are unavailable. This flexibility allows robots to provide critical services in difficult-to-reach places.

9. Another advantage of IoT is its focus on energy efficiency. IoT protocols are designed to optimize device operations and minimize power consumption. This is particularly crucial for robots that operate in energy-constrained environments. In space exploration or environmental monitoring, for instance, solar-powered eco-robots rely on IoTs low-power communication to function autonomously for extended periods without needing constant human intervention. These energy- efficient protocols allow robots to perform their tasks reliably without frequent recharging or maintenance.

10. Finally, security and privacy are paramount in IoT systems, especially when it comes to sensitive sectors like healthcare or defense. IoT uses end-to-end encryption and secure protocols to protect data and ensure that robotic systems remain safe from cyberattacks. In military applications, for example, secure IoT communication ensures that field robots can carry out their missions without the risk of interference. In healthcare, IoT- enabled robots that handle patient data employ strong security measures to safeguard sensitive medical information, maintaining trust and compliance with privacy regulations. These features demonstrate how IoT is transforming the capabilities and applications of robotics, making tem smarter, more efficient, and adaptable across a wide range of industries.

Fig.1 presents the features of IoT, showcasing various aspects such as connectivity, sensors, actuators, and scalability within the IoT ecosystem.

Key Advancements in IoT-Driven Robotics

1. Enhanced Industrial Automation: IoT-integrated robotics is revolutionizing manufacturing with real-time process monitoring, precision in defect detection through machine vision, and optimized production efficiency. This reduces downtime and hardware footprint while increasing productivity

   Figure 2 : AIIoT in robotics applications. (source:researchpaper[16])

2. Internet of Robotic Things (IoRT): The synergy between IoT and robotics, known as IoRT, enables robots to autonomously gather, analyze sensor data, and interact with their environment. This integration enhances robot intelligence, functionality, and decision-making across various industries.

3. Collaborative Robots (Cobots): Cobots are designed to safely work alongside humans, enhancing productivity in shared

   spaces. Supported by advancements like 5G for rapid decision- making, cobots are transforming industrial and safety-critical environments without compromising human safety.

4. Smart Agriculture and Sectoral Applications: IoT-driven robotics is leading innovations in agriculture by automating labor-intensive tasks and improving efficiency. Additionally, IoRT systems are making significant contributions in healthcare, education, and surveillance, improving societal and economic outcomes.

5. AI and Ethical Considerations: The integration of AI with IoT in robotics boosts automation, adaptability, and operational efficiency across sectors. However, this advancement also brings ethical challenges, particularly in job displacement and ensuring ethical programming in autonomous systems, especially in sensitive fields like healthcare.

Practical Applications

1. Smart Manufacturing: IoT-driven robots are used in factories for tasks like assembly, quality control, and packaging. These robots can monitor production in real-time, detect defects with machine vision, and make adjustments on the fly, leading to higher efficiency and reduced waste.

2. Precision Agriculture: Robots equipped with IoT systems automate tasks such as planting, watering, and harvesting crops. These systems can monitor soil conditions, detect pests, and optimize resource use, improving crop yields while reducing labor and costs.

3. Healthcare Assistance: In healthcare, IoT-driven robots assist with surgeries, patient care, and rehabilitation. They can monitor patients vital signs, deliver medication, and even help in physical therapy, improving patient outcomes and easing the workload of healthcare professionals.

4. Collaborative Workspaces: Cobots work alongside human workers in environments like assembly lines and logistics centers. They handle repetitive or physically demanding tasks, enhancing productivity while ensuring safety through advanced sensors and real-time decision-making.

5. Surveillance and Security: IoRT-enabled robots are used for surveillance in both public and private sectors. These robots can monitor areas, detect unusual activity, and respond to security threats autonomously, providing a new level of security and safety.

IOT-AIDED ROBOT APPLICATIONS

The synergy of IoT and robotics remains largely an untapped field of future technology that has the potential to bring about drastic changes to how we live today. IoT based solutions are changing the way we tackle problems. Smart homes, wearables, smart cities, smart grids, industrial internet, connected cars, connected health, smart retail, smart supply chains and smart farming are only a few of the IoT applications in todays times which have impacted how we live as a society. By providing real time, quantifiable and decisive data, IoT has reduced our response time to critical problems and in a few cases made removed the need for human supervision to solve problems. Robotics, on the other hand is a field of science that has been held back the technology of its time. To top it off, the investment required to deploy robotics based solutions is high. This is however changing.

Robotics based solutions to challenges are quickly emerging. Industrial robots, used in the manufacturing and automobile industry have reduced production time, reduced degree of error and improved quality produce. Robots are used for deep underwater explorations and unchartered space explorations. In this section, Ill be focussing on the amalgamation of IoT and robotics applications/solutions in healthcare, industry, military and search and rescue operations.

1. Healthcare applications: IoT applications in the healthcare industry range from remote monitoring of patients. Wireless devices that monitor the patients vitals are connected together in Wireless Body Area Network, that deliver the collected data to a remote device for monitoring, tracking and analysis. Edge devices that gather timely data of the patient, allow healthcare providers to remotely monitor, assist and if possible provide medication to those patients for whom it may not be feasible to meet their healthcare provider. Robotics in healthcare is mostly seen in literature and there is little widely in practice today. IoT and robotics solutions can deployed to provide assistance to disabled, elderly patients and those with locomotory issues[. Monitoring and tracking of medical equipment or lack of can greatly improve management of hospitals and medical equipment so that less amount of time goes into maintaining infrastructure. This can greatly improve the quality of medical service that is dispensed to patients.

   Fig 3. IoT in healthcare ( source:Quytech)

2. Industrial Applications and Personal Applications: IoT solutions solve a wide range of problems in industry from electrical grid system monitoring, temperature monitoring, power consumption, lubricant status, etc.Fig.4 explains the various applications of iot in industrial aspect. IoT applications are also often used in perimeter intrusions detection systems at airports, railway stations and ship ports. Smart objects are used to manage parking places. Smart objects comprising the wireless sensor network (WSN) are used enable automation, energy monitoring and control and surveillance systems. Robots in industry are largely used in large assembly lines to speed up the production process. Robotic perception along with artificial intelligence are used for efficient human robot interaction. Moving toward the vision of a robot in the personal space, cleaning and servicing robots are increasingly becoming common trend. Efforts are being made to deploy robots in the public space for surveillance and monitoring activities. IoT aided robotics are most suitable for scenarios where real time data is required from inhospitable environments for long durations of time. IoT aided robots can be strategically deployed to get high quality real time data which would not have possible from disconnected robots.

   Fig 4. IoT in IndustriAutomation (source:-Rishabh software)

3. Military Applications: IoT in the military is used to detect presence and intrusion of unwanted chemical agents, signals, radiations etc though photoelectric, laser and acoustic sensors. They are used to uncover hidden areas of danger, track enemy movements, detect snipers and perform perimetric surveillance in sensitive areas. The most common type of robotic military application would be the unmanned aerial, ground, and underwater vehicle.refer fig.5 These robots are use to cover areas which would normally put the life of manysoldiers at risk. Using these, remote surveillance and attack can be carried out over crucial strategic zones. IoT aided robot applications can include the co-ordination of smart objects with UAVs, UGvs and UUVs. Smart objects can detect and uncover chemical agents, hazard zones and nuclear/biological weapons in the given environment, these can then be traversed by UGV/UAV/UUV to further evaluate and monitor the environment.

   Fig 5. Military Application (source – Indeema software)

4. Rescue Applications Smart objects in are used to collect emergency information and distribute the captured data to the required sources in the least amount of time as possible. IoT devices operating in a wireless sensor network are ideal in disaster scenarios to relay critical information as the default communication infrastructure may be damaged. They are used to monitor the relief and rescue operations of the affected site. This information can be used to organize and direct ground rescue forces to critical areas. Robot applications in recure are used in search and rescue, where it is too dangerous or not physically possible for rescue and relief forces to save people. IoT aided robot applications can be used to coordinate with relief and rescue forces on the ground to prioritize operations according to risk and damage to the environment and then to deploy robot applications to perform search and rescue operations on high priority locations. The following section discusses the use case of an Intelligent Transportation System within an IoRT architecture.

5. Space Applications: Space robots communication involves networking multiple UAVs for tasks like border surveillance, disaster monitoring, and emergency rescue. UAVs require robust wireless networks to coordinate actions and maintain real-time communication through air-to-air and air-to-ground links. Technologies like IEEE 802.15.4, Wi-Fi, and 3G/LTE are commonly used, but they have limitations. Flying Ad Hoc Networks (FANETs) address unique challenges such as limited flight time, bandwidth, and latency. Advanced clustering algorithms like Energy-Aware Link-based Clustering (EALC) and hybrid methods combining Glowworm Swarm Optimization (GSO) with krill herd algorithms improve routing efficiency, energy consumption, and communication stability, essential for UAV performance in dynamic environments.

   Fig. Space Application (source – New Space Economy)

6. Marine Application: Underwater robot communication is crucial for tasks like disaster prediction, maritime surveillance, navigation, and oil exploration. Due to the limitations of electromagnetic signals underwater, acoustic signals are commonly used, offering long-range communication but with challenges like ambient noise, high latency, and limited bandwidth. Visible Light Communication (VLC) provides faster data rates but works only over short distances. Another alternative is radio frequency, but it requires large antennas and covers limited ranges. Advanced research focuses on cognitive communication systems that dynamically adjust parameters like frequency and encoding to suit environmental conditions. The Centre for Maritime Research and Experimentation (CMRE) is developing a fully adaptive communication architecture for underwater networks. Future solutions aim to create more efficient, adaptable networks, ensuring reliable data transmission in harsh environments such as deep seas, caves, and dense aquatic regions, ultimately improving the performance and safety of underwater autonomous vehicles and Unmanned Underwater Vehicles (UUVs).

Fig. Marine Application (source – reference paper [15])

CONCLUSION:

The integration of IoT with robotics has significantly transformed various industries, enabling smarter, more efficient, and autonomous systems. From manufacturing and agriculture to healthcare and logistics, IoT-aided robots are enhancing productivity, optimizing resource use, and improving the quality of services. As these technologies continue to evolve, they will play an increasingly critical role in shaping the future of automation, offering innovative solutions to complex challenges while also raising important considerations around ethics, job displacement, and security. The ongoing advancements in IoT-driven robotics promise to revolutionize our daily lives and industries, driving us towards a more connected and intelligent world.

REFERENCES:

1. A. Chauhan, S.K. Jakhar, C. Chauhan, The interplay of circular economy with industry 4.0 enabled smart city drivers of healthcare waste disposal, J. Cleaner Prod. 279 (2021) 123854. 71 M. Javaid, A. Haleem, R.P. Singh et al. Cognitive Robotics 1 (2021) 5875

2. L. Gualtieri, E. Rauch, R. Vidoni, Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review, Rob. Comput. Integr. Manuf. 67 (2021) 101998.

3. Liyakat, K. K. S. (2023, March). Machine learning approach using artificial neural networks to detect malicious nodes in IoT networks. In International Conference on Machine Learning, IoT and Big Data (pp. 123- 134). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981- 99-3932-9_12

4. Pradeepa, M., Jamberi, K., Sajith, S., Bai, M. R., & Prakash, A. (2022, October). Student health detection using a machine learning approach and IoT. In 2022 IEEE 2nd Mysore sub section International Conference (MysuruCon) (pp. 1-5). IEEE. https://doi.org/10.1109/MysuruCon55714.2 022.9972445

5. L. Zhang, I. K. Dabipi, and W. L. Brown, Internet of Things applications for agriculture, in Internet of Things A to Z: Technologies and Applications,

   Q. Hassan, Ed., 2018.

6. S. Navulur and M. N. Giri Prasad, Agricultural management through wireless sensors and Internet of Things, Int. J. Elect. Comput. Eng., vol. 7, no. 6, pp. 34923499, 2017.

7. Shih, C.S.; Chou, J.J.; Reijers, N.; Kuo, T.W. Designing CPS/IoT applications for smart buildings and cities. IET Cyber Phys. Syst. Theory Appl. 2016, 1, 312.

8. Saeed, N.; Elzanaty, A.; Almorad, H.; Dahrouj, H.; Al-Naffouri, T.Y.; Alouini, M. CubeSat Communications: Recent Advances and Future Challenges. IEEE Commun. Surv. Tutor. 2020, 22, 18391862.

9. Intelligent Transportation Systems. https://en.wikipedia.org/wiki/Intelligent transportation system (accessed January 2, 2017).

10. Ticllacuri, V.M.; Cornejo, J.; Jamanca-Lino, G.; Diaz, A.; Castrejon, N.; Dev, D.; Chen, Y.K. Design of Wearable Soft Robotic System for Gait Muscles Stimulation during Lunar Colonization. In Proceedings of the 2021 CHI Workshop on Human-Computer Interaction for Space Exploration (SpaceCHI), Virtual Conference, 21 May 2021; ACM: New York, NY, USA, 2021.

11. Morgan Quigley and Brian Gerkey. ROS: an open-source Robot Operating System. ICRA Workshop on Open Source Software, 2009.

12. D. Villa, X. Song, M. Heim, L. Li, Internet of robotic things: current technologies, applications, challenges and future directions, arXiv preprint, arXiv:2101.06256, 2021, 18.

13. R. Doriya, S. Mishra, S. Gupta, A brief survey and analysis of multi-robot communication and coordination, in: International Conference on Computing, Communication & Automation, IEEE, 2015, pp. 10141021.

14. J. Wang, C. Peng, Y. Zhao, R. Ye, J. Hong, H. Huang, L. Chen,

    Application of a robotic tele-echography system for covid-19 pneumonia, J. Ultrasound Medicine 40 (2) (2021) 385390

15. Kabanov, Aleksey, and Vadim Kramar. "Marine internet of things platforms for interoperability of marine obotic agents: An overview of concepts and architectures." Journal of Marine Science and Engineering 10, no. 9 (2022): 1279.

16. Dhanwe, Sunil Shivaji, Chopade Mallikarjun Abhangrao, and Kazi Kutubuddin Sayyad Liyakat. "AI-driven IoT in Robotics: A Review." Journal of Mechanical Robotics 9, no. 1 (2024): 41-48.