Track Categories

The track category is the heading under which your abstract will be reviewed and later published in the conference printed matters if accepted. During the submission process, you will be asked to select one track category for your abstract.

Robotics is a convergence of engineering and technology that covers mechanical engineering, electrical engineering, computer science, and other engineering fields. Robotics is one of the industry's newest rising sectors. Robots are being used in almost every industry to simplify circumstances. A robotic process necessitates the use of both software and physical components, including a power source, actuators, sensors, locomotive parts, storage devices, and control software. Robotics is currently widely employed in the military, security, construction, and medical, agricultural, home, and educational fields.

People's lives are made easier by robotics. There is a strong possibility that robots will be used in every household in the future. Both autonomous and manual robots are important in robotics.

Artificial intelligence is a discipline of software engineering that focuses on constructing intelligent robots that behave and react similarly to humans. Artificial intelligence is skilled at analyzing how the human brain makes decisions, learns, and functions when attempting to solve a problem. It then uses the findings of this analysis to create increasingly intelligent software and systems. Knowledge has several unpleasant traits in real life. Hardware-driven, robotic automation is different from AI. Instead of automating manual labour, artificial intelligence executes frequent, high-capacity, electronic jobs reliably and without getting tired. In the modern world, artificial intelligence (AI) may be used to operate robots, sensors, actuators, and other devices in a number of ways.

People are now aware of the unique benefits of using robots for medical reasons as a result of recent advances in medical robotic research. Robotic systems' ability to perform a variety of clinical and other medical tasks with high accuracy and repeatability, as well as their capacity to give doctors better visual feedback, are the key factors that have attracted so much attention to them. Robotics research and use in medical settings have increased as a result of their advantages and capabilities in clinical settings. As medical robotic technology has advanced, there are now more medical robots on the market and more of them are being used in actual clinical settings. Robots are anticipated to play significant roles in modern medical diagnostics, surgery, rehabilitation, drug delivery and other procedures in the future.

We currently live in the age of the intelligent machine. Robots now play a diverse and active part in our daily lives. It appears that the scientific mechanism is becoming a fact. Since there is good technology to oversee the functions of their home, robots are gradually approaching us. Within the next ten to fifteen years, there's a significant chance that robots will be working in the homes of regular people as technology continues to advance. The session's major topic of discussion is how robots become significant allies on our path and how they assist us in making positive changes in our lives.

A data-organizing perspective called an Artificial Neural Network (ANN) is dictated by the way that organic sensory systems work. Artificial neural networks use computers to carry out specialised tasks like pattern recognition and clustering. Similar to human brains, they acquire knowledge through learning, and that knowledge is stored within the strengths of interneuron connections. Through a learning process, an Artificial Neural Network is created for a specific purpose, such as design acknowledgment or information organisation. They are able to simultaneously process and model nonlinear relationships between inputs and outputs.

They stand out for having adjustable weights along the connections between neurons that may be adjusted by a learning algorithm that gains knowledge from observed data to enhance the model. Artificial intelligence's Deep Learning function simulates how the human brain processes data and generates designs for use in decision-making. Deep learning is a branch of machine learning that is focused on the description of learning data. It is structured learning. For training via back propagation, it makes use of some kind of inclination extraction. In deep learning, sets of propositional formulas and hidden layers of artificial neural networks are utilised as layers.

Data Analytics examines and analyzes huge amounts of data, i.e Big data to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help companies make more informed business decisions. Software can pave the way for Data Analytics to deliver various business benefits, including new revenue opportunities, more effective marketing, improved operational efficiencies, competitive advantages, and better customer service

Data science is the study that combines domain knowledge, programming abilities, and math and statistics understanding to extract useful insights from data. Machine learning algorithms are used with numbers, text, photos, video, audio, and other data to create artificial intelligence (AI) systems that can execute jobs that would normally need human intellect. As a result, these systems produce insights that analysts and business users may employ to create meaningful commercial value.

Big Data is a collection of statistics that is large in volume yet grows rapidly over time. It is a statistic of such enormous length and complexity that no ordinary statistics control equipment can effectively store or process it. Big statistics are similar to statistics, except they are much longer. Experimentation and inquiry are required to effectively exploit the benefits of Big Data

The previous several years have seen a lot of buzz surrounding block chain and machine learning (ML), but not as much in tandem. Block chain can handle nearly any kind of transaction because it is a distributed ledger. Its fast rising popularity and power are primarily due to this. The transaction recording procedure will be sped up and made simpler with the help of the block chain.

This means that utilising this entirely decentralised system, any kind of asset can be transparently traded. The main distinction is that there are no middlemen involved here, such as the government, banks, or even technology firms. Rather, it's a large collaboration with excellent code that drastically cuts settlement and clearing times to a matter of seconds.

By 2024, the total amount spent on artificial intelligence (AI) will be $40.6 billion. The creative advancement provided by AI technologies has just come to light. Health is not protected, and these changes may progress numerous procedures. Health, health data quality evaluation, personalised health with sensor data, cross-source learning for improved lifestyles, and health data visualisation are just a few of the many study opportunities that the remarkable developments in healthcare have opened up. The development of AI in the area of customer benefit and the challenge posed by AI calculations are expected to transform the field of financial management.   

The network of physical items, or "things," that are implanted with sensors, software, and other technologies for the purpose of communicating and exchanging data with other devices and systems through the internet is referred to as the Internet of Things (IoT).

These gadgets include anything from common domestic items to high-tech industrial gear. Today, there are more than 7 billion connected IoT devices, and according to analysts, there will be 10 billion by 2020 and 22 billion by 2025. Device partners are part of Oracle's network. IoT has emerged in recent years as one of the most significant 21st-century technologies. Continuous communication between people, processes, and things is now possible thanks to the ability to connect commonplace items—such as household appliances, automobiles, thermostats, and baby monitors—to the internet via embedded devices.

Robots that resemble humans are becoming more and more common in India. Indian start-ups and the government are moving quickly to integrate new technology, even if the nation is still catching up to other nations in terms of robotics and artificial intelligence advancements.

Robot sales in India reached a new high of 2,627 units, up 27%, according to IFR research, which is almost the same as Thailand. According to another study, India is third in the world for using robotic automation.

The branch of study known as "computer vision," or CV for short, aims to create methods that will enable computers to "see" and comprehend the content of digital images like pictures and movies.

Because everyone, including very young toddlers, can trivially solve the computer vision issue, it looks to be an easy one. However, because to our incomplete understanding of biological vision and the intricacy of visual perception in a dynamic physical world with almost endless variation, the topic generally remains unanswered.

Advanced cloud technologies are the focus of the robotics subfield known as cloud robotics. Cloud robotics can be used to learn about cloud computing, cloud storage, and other Internet technologies focused on the advantages of converged infrastructure and shared services for robots. Robots that are connected to the cloud can benefit from the advanced processing, storage, and communication capabilities of a cloud data centre that can handle and exchange data from numerous robots or agents. Through networks, humans can assign duties to robots remotely as well. These cloud computing technologies allow robot systems to be equipped with strong capabilities while also lowering costs. As a result, it is conceivable to develop cheaper, lighter, and smarter robots that are "brain-powered" by the cloud. 

For deep learning, information processing, environment modelling, communication support, etc., the brain in the cloud is crucial and responsible. Although there are many benefits of cloud computing for robots, the cloud is not a panacea for all robotic problems. Robot movement control that heavily relies on (real-time) sensors and controller feedback may not really benefit from the cloud. Real-time execution tasks necessitate onboard processing. High-latency replies or network issues can also cause cloud-based applications to lag or become unavailable. Robots that rely too heavily on the cloud could become "brainless" if the network experiences a problem

Artificial intelligence will change how we view the world in this period in a variety of ways. Using intelligent automation and artificial intelligence, businesses may increase productivity and effectiveness, lower operational risks, and enhance customer engagement. In intelligence automation, we employ computer programmes or other technology that can carry out tasks autonomously. This seminar examines how artificial intelligence and automation are being used extensively to improve human life. Since 1930, people have started to believe in industrial robots. In 1954, the first manufacturing robot was used. Since robots have opened up new job chances in other areas while also granting some jobs in manufacturing.

Robots typically perform tasks like welding, painting, assembling, pick-and-place packing, labelling, etc. in the industrial sector. The session has been specifically designed for people who work in various industries as well as students who will eventually work in those fields. Business organisations will also benefit from looking at some of the newest technologies developing in these fields.

One area of biomedical engineering that has a specific focus is rehabilitation robots. In this area, engineers, therapists, and clinicians work together to assist patients recover. The field's top priorities include creating implementable technologies that are simple for patients, therapists, and clinicians to use. By improving the effectiveness of clinicians' therapies, this will make it easier for patients to go about their daily lives. The number of rehabilitation robots has grown over the last ten years, however due to clinical trials, their capabilities are quite limited. Many clinics have conducted trials but have chosen not to deploy the robots because they would prefer that they be remotely operated. Making robots engaged in a patient's rehabilitation offers certain benefits.

The fact that you can repeat the process as many as you like is one of its benefits. You can obtain precise measurements of their advancement or deterioration, which is another advantageous element. Using the device's sensors, you may obtain the precise measurements. One must use caution as the robot prepares to take measurements because it could be interfered with. Long-term continual therapy can be administered by the rehabilitation robot. Many therapists, scientists, and patients who have received the therapy agree that the rehabilitation robot is an effective tool to use. He is unable to comprehend the patient's demands during the healing process like a skilled therapist would. Currently, the robot cannot understand, however in the future, the device will be able to understand. Another advantage of having a rehabilitation robot is that there will be no physical effortput into work by the therapist.

Researchers have been working on silicon chips that can directly integrate neural network design as a result of the popularity of Deep Learning concepts that rely on neuron-based models. At the hardware level, these chips are programmed to simulate the human brain. In a typical chip, data must typically be transported between the central processing unit and storage blocks, which uses energy and adds time overhead. In a neuromorphic semiconductor, data is assembled and stored analogously, and it can create synapses as needed to conserve time and energy.

Recent years have demonstrated the crucial advancement that multimedia and AI technology have provided. Many sectors and behaviours can advance as a result of these changes, and health is not an exception. Due to the abundance of multi-model sensors and smart objects in the environment, greater multimedia collaboration among many organisations, and real-time media sharing amongst socially connected individuals, multimedia plays a dynamic role in the eco-system of smarter cities. Given that it offers a customizable stack of computing, storage, and software services at a reasonable price, cloud computing Events is a good choice as an enabling technology in this situation. We are currently seeing a common trend toward multimedia cloud computing, where the computationally intensive parts of multimedia systems, services, and apps are shifting into the cloud, and the end user's mobile device is being used as an interface for accessing those services.

Laparoscopy, neurosurgery, orthopaedic surgery, emergency response, and many more areas of medicine are now impacted by robots. The capabilities of existing medical robot systems, with a primary focus on systems that are readily accessible on the market and a brief discussion of several significant research initiatives.

Trends that suggest future capabilities of medical robots can be seen by comparing robotic systems across disciplines and time, such as greater intraoperative image use, enhanced robot arm design, and haptic feedback to assist the surgeon.

A recent development in robotic systems is the network robotic system. Three levels make up the hierarchical control scheme: learning level, skill level, and adaption level. The learning stage manipulates symbols to arrive at control methods logically.

Along with control tactics and environmental sensory data, the skill level also generates control references. The level of adaptability regulates robots and machines as they adjust to uncertain situations. Artificial intelligence, neural networks, fuzzy logic, and evolutionary algorithms are applied to the hierarchical control system while integrating and synthesising themselves for these levels and to connect them.

Intelligent devices that function at the micrometre size are known as micro robots. The micron-sized robots were created and put together using equipment and procedures created by IRIS researchers. Numerous of these systems are employed for robotic exploration of biological domains, including the study of cellular and molecular behaviour and molecular structures.

Although research into small-scale robotics is starting to approach these proportions, nano-robots are still a thing of science fantasy. Robots that are large enough to manipulate items with nanometer resolution or robots that are nanoscale in size are referred to as nano robots. Nano electromechanical Systems, or NEMS, are made possible by nano robotic manipulation.

Artificial intelligence (AI) in the future has the potential to revolutionise society. Computers have advanced greatly since the introduction of the Turing Analysis. Artificial intelligence is rapidly becoming a significant economic force. Without a doubt, it will play a crucial role in human life in the future. But there is still a crucial question: what would happen if the creation of robust artificial intelligence is successful and a machine learns to outperform humans? We are confident that this meeting will enable us to talk about, improve, and steer clear of such potential results in the future.

Natural Language Processing is essential for translating commands from human language to computers and the other way around. This method makes it simple for humans and robots to communicate. In other words, natural language processing converts organised knowledge into human language. Visit our Robotics and Al 2023 conference for additional details.

Robots currently carry out a variety of occupations across several industries, and the number of tasks assigned to them is steadily growing. A division based on the use of the robots is the most effective method of categorising them.