The IoT and robotics, two different fields, are coming together to create IoRT (Internet of Robotic Things). The IoRT is a concept in which intelligent devices can monitor the events happening around them, fuse their sensor data, use local and distributed intelligence to decide on courses of action, and then bet have to manipulate or control objects in the physical world.
In IoRT, robotic things can communicate with other things. It exchange/share information with other robotic things, IoT/IIoT devices, and humans in various applications. We design IoT devices to handle a specific task. while robots need to react to unexpected conditions. Artificial intelligence and machine learning help these robots deal with unforeseen situations that arise.
Robotic things are capable of recognizing events and changes in their surroundings. While autonomously acting and reacting appropriately. These capabilities enable the convergence of the real, digital, virtual, cyber attributes of robotic things. Smart environments that make robotic things in energy, mobility, buildings, manufacturing, and other sectors more intelligent.
Similarities and Differences
Robots and IoT devices are similar in that they both rely on sensors to understand their environment. Rapidly process large streams of data, and decide how to respond.
Most IoT applications handle well-defined tasks, whereas robots autonomously handle anticipated situations. Robotic devices are controlled as per the command and not linked to the internet. Whereas we control/maintain IoT devices through the internet.
Explanation of IoRT
So far, the robotics and IoT communities have been driven by varying yet highly related objectives. IoT focuses on supporting services sensing, monitoring, and tracking. Data gathering, analytics, communication, and the cloud leverage the data from somewhat passive sensors.
In contrast, robotic focus on production action, interaction, and autonomous behavior. The IoRT(Internet of robotics things) adds a substantial value by combining the two fields.
- First, the robot can sense that it has embedded monitoring capabilities. Simultaneously, it can get sensor data from other sources.
- Second, it can analyze data from the event it monitors, which means there is edge computing. Edge computing is where data is processed and analyzed locally instead of in the cloud. And it eliminates the need to transmit a wealth of data to the cloud.
- Finally, both primary components serve the third one, determining what action to take and take that action. It can control or manipulate the physical object in the physical world. Collaborations between machine and machine, and between man and machine.
Applications of IoRT
It uses sensors, middleware, deep learning, edge computing, and more to enable industrial robotics devices that coordinate and collaborate. Industrial collaborative robots are one of the main areas in IoRT. Robots bound with IoT can take active participation while solving numerous problem fields such as health care, infrastructural maintenance, EC sites, departmental stores, life-critical situations, data centers, business shows, WSDL interface, and many more. The possibilities are countless and ever-growing, hence its importance and existence.
Use cases
- IoT based remotely operated vehicle
- Collaborative robots
- Drones for industries
- Inspection robots
- Drones for agriculture
- Personal robots
- machine to machine connected robotic devices
- healthcare and bio-tech devices
