A paradigm shift in automation is being brought about by the Internet of Robotic Things at a time when technology is still evolving at an unheard-of rate. IoRT combines the IoT and robotics technologies’ promise to transform industries, boost automation, and improve daily living. Manufacturing, healthcare, transportation, agriculture, and smart cities are just a few of the sectors where the Internet of Things is changing conventional practises and setting the framework for a more connected and intelligent future.
In conversation with Jignesh Karia, Distinguished Engineer | CTO – Telecom Cloud, IBM to know more about the recent advancements in the Internet of Robotic Things, their impact on the fields of health, science, agriculture, manufacturing, education, and surveillance, as well as the challenges surrounding the integration of robot technology into intelligent settings
How is the Internet of Robotic Things (IoRT) shaping the future of automation and robotics?
The Internet of Robotic Things represents a paradigm shift in automation, combining the power of IoT and robotics. IoRT is positioned to transform industries and fundamentally alter how people live and work in a variety of sectors, including manufacturing, healthcare, agriculture, and smart cities. Through seamless connectivity, real-time data-driven decision-making, collaboration, and autonomous systems, IoRT is reinventing the future and increasing productivity, scalability, and effectiveness. Robots can get real-time data from sensors. The study of this data can provide information that can be used to improve robotic decision-making, restructure corporate operations, and reduce operational costs. Leading academics claim that IoRT can reduce operating costs for companies by up to 25%. IoRT holds the key to an automated future by making intelligent, linked robotic systems possible.
Can you share some examples of how advanced smart machines are being integrated into the IoRT to improve manufacturing and other industries?
A recurring theme in our conversations with clients of all sizes in the industrial industry is how IoRT’s integration of cutting-edge smart equipment is upending traditional business models and creating new opportunities for innovation and expansion. A few examples include IoRT tracks data on machine performance in real-time to give production floor operations predictive maintenance. Data analysis and machine learning (ML) can be used to find potential errors, enabling planned maintenance, and reducing unplanned downtime.
The IoRT combines current machine learning techniques with modern visual technologies to automate quality inspection processes. Using cameras, sensors, and AI algorithms, these gadgets inspect objects for faults, determine their dimensions, and judge their quality.
Similarly, IIoT sensors when connected to the IoRT, provide important insights into machine performance, health monitoring, and quality control. Making proactive decisions is made possible by this information.
Digital twins provide real-time monitoring and analysis of physical equipment when used in conjunction with the IoRT. Manufacturers can optimise operations and simulate various situations with the use of predictive analytics.
By employing real-time data analysis and decision-making, manufacturing organisations may improve overall production efficiency, reduce human error, and maintain consistent quality. According to studies, the usage of IoRT and smart equipment increased labour productivity by 10% while reducing expenses by 12%.
How important is it for robotics and automation to work in sync, and what challenges need to be addressed to achieve this?
Robotics and automation must work together to make it possible for robotic systems to communicate, connect, and be controlled in an efficient and reliable manner. Effective communication guarantees the timely transmission of control instructions, sensor data, and other vital information, enabling the coordinated control and operation of robotic equipment. Synchronisation improves robotic system productivity and overall performance, helping to maintain the desired level of service.
IoRT offers enormous potential, but there are certain major issues that must be resolved to ensure effective coordination.
Efficient automation: It is crucial to develop effective & efficient AI models that can recognise and respond to problems related to synchronised activities, such as collisions, interactions between humans and robots, and system failures.
Optimised network: For efficient coordination, it’s crucial to have a dependable and strong network infrastructure. To keep robotic devices and the network connected continuously, telcos must handle problems including network outages, signal interference, and system malfunctions.
Data security: Ensure the integrity and confidentiality of data exchanged between robots and the network by implementing strong cybersecurity measures to guard against potential dangers like unauthorised access, data breaches, or malicious attacks.
While IoRT presents immense possibilities, it also comes with challenges. Security, privacy, and interoperability of robotic systems need to be addressed to ensure reliable and safe operation. Additionally, ethical considerations surrounding autonomous decision-making by robots require careful deliberation.
With the increasing adoption of robotics and automation, what are some of the skills that will be in demand in the workforce?
As robotics and automation continue to advance and become more prevalent, several skills will be in high demand in the workforce.
Robotics engineering: Proficiency in robotics engineering will be crucial, including knowledge of robot design, programming, and system integration. Skills in areas such as robot perception, motion planning, control systems, and sensor integration will be highly sought after.
Software development: Strong programming skills will be essential, particularly in languages commonly used in robotics, such as Python, C++, or MATLAB. Proficiency in software development for robotics applications, including algorithms, simulations, and machine learning, will be in demand.
AI & machine learning: Development of intelligent systems and the learning and adaptation capabilities of robots will be made possible by an understanding of algorithms, neural networks, and deep learning approaches.
Data science and analytics: As IoT and robotics proliferate and generate massive volumes of data, skills in data science and analytics will be vital. Insight extraction, pattern analysis, and data-driven decision-making will all be important for optimising robotic systems and procedures.
Cybersecurity and robotics safety: As robots and automation become more interconnected, cybersecurity professionals will be needed to defend systems against online threats. Additionally, knowledge in risk analysis, fault detection, and fail-safe procedures will be essential for assuring the security of robotic systems.
How do you envision the future of the IoRT and its impact on industries such as manufacturing, healthcare, and transportation?
The future of the Internet of Robotic Things (IoRT) holds immense potential for further advancements and transformative impacts across various industries. IoRT is positioned to transform industries and fundamentally alter how people live and work in a variety of sectors, including manufacturing, healthcare, agriculture, and smart cities. The IoRT has the power to transform several fields and businesses. Applications of it include:
Healthcare:Â In the healthcare industry, IoRT plays a significant role in areas such as robotic surgery, telemedicine, remote patient monitoring, and medication management. Connected medical devices and robotic systems can collaborate to provide better diagnostics, more precise surgeries, and personalised patient care.
Manufacturing: In the manufacturing industry, IoRT is transforming operations and driving efficiency gains. With the integration of robots into the IoT ecosystem, manufacturers can achieve enhanced connectivity, real-time data analysis, and autonomous decision-making. Robots equipped with advanced sensors and automation can monitor production lines in real time. They can detect defects, variations, or anomalies, enabling immediate corrective actions. This improves product quality and reduces waste.
Transportation: The transportation sector is being transformed by IoRT, which is revolutionising fleet management, logistics, and autonomous vehicles. In order for autonomous vehicles to collect and interpret real-time data from sensors, cameras, and GPS, IoRT is a critical enabler. Using this information, autonomous vehicles may be able to make sensible decisions, navigate correctly, and improve traffic safety. IoRT offers intelligent traffic management systems that rely on real-time information from vehicles, IoT sensors, and infrastructure. Utilising this information will enhance traffic flow, reduce congestion, and boost the efficiency of transportation. Robots connected to the Internet of Things (IoT) can optimise logistics and supply chains while also enhancing warehouse operations, inventory management, and logistics processes. IoRT makes it possible to remotely monitor and maintain fleets of vehicles.