Good quality sensor data is crucial for IIoT applications
Published on : Saturday 04-09-2021
Jegajith P T, Embedded Practice Head, Utthunga.
What are the roles sensors are performing in the field of industrial automation today?
Sensors are the key elements used in almost every intelligent device in industrial automation. The ability to gather critical field device information has allowed sensors to be deployed to simplify and automate industrial processes in multiple ways. Diagnosing the assets’ health status by means of signal noise to prevent failures, triggering alarms for functional safety, etc., are some of the important operational aspects taken by the sensors. Beginning with condition-based monitoring and power management, to image sensing and environment monitoring, the list is just endless.
Cheaper, low-cost sensors are getting popular. Is there a trade-off here and the implications?
True. Sensors are becoming more cost-efficient because these are produced in mass. This also implies that the usage of sensors is going to increase exponentially. As far as the low cost sensors are concerned, the quality issues will always exist posing challenges in maintaining the sensor lifetime. Limited durability, difficulty in data management/analysis, etc., are some of the primary challenges faced when low-cost sensors are deployed. A factor that would help reach cost and productivity trade-off is ‘downtime’. As downtime reduces, the maintenance cost also reduces, causing increased sensor productivity.
At the other end, sensors are getting smarter. What exactly is smart about a smart sensor? Is it really smart to opt for a smart sensor?
Smart sensors are trending in the industrial world. The feature that makes a sensor smart is the use of a microcontroller and FPGA to handle the logic operations and take certain actions or store various configurations that can be modified to change specific parameters. TinyML is gradually catching pace to make small embedded devices even smarter.
Coming to the next question, yes, deploying a smart sensor is a smart decision. Let’s try to understand this with an example, say a Proximity Detection Sensor. A proximity detection sensor can be configured to trigger distance-based alarms for conveyor belt applications. Similarly, Vibration Sensors are capable of filtering the vibration signals, raising alarms, and taking corrective measures for various load balancing activities in moving platforms with the help of Tiny Machine Learning algorithms. These types of trends in sensor technology are allowing sensor technology to take the centre stage in the embedded engineering world.
The topics of digital transformation like data analytics and AI/ML all depend on the availability of 'good' data. What are the advancements in sensor technology to capture data which is difficult to obtain?
Good quality sensor data is crucial for IIoT applications as missing data and poor quality data can cause errors in detection and prediction processes. To deal with scenarios that are unusual, the datasets for abnormal instances can be created in a training environment and a reinforcement algorithm can be developed from the existing dataset to make prediction and enable accuracy.
It would be highly desirable that electric vehicles transmit more data back to stations to enable new business models. What are the demands on sensors in moving vehicles?
Sensor technology has massive implications in transportation in general. Ranging from traffic control, to safety, navigation, and entertainment, sensors are used in developing an array of applications for modern vehicles. If the trends are to be believed, autonomous vehicles are soon going to witness exponential growth. Automakers from across the globe are touting the importance of electrified vehicles and are racing to be early adopters. Remarkably, high quality sensors like displacement sensors, inertial sensors, RADAR sensors, proximity, ultrasonic, and electromagnetic sensors are used in multiple EV applications like safety, parking assistance, vehicle, and component orientation feedback, real-time navigation, etc.
Consider a connected electric pedal assist bicycle. The pedal count V/S the force feedback can act as the fitness information to the rider. Similarly, the driving pattern of an electric vehicle can predict the battery life, temperature dissipation of the battery, and motor.
What are the emerging trends in sensors that will further increase efficiency?
Transducers are key elements of sensors. These transducers are becoming smart with modern semiconductor based transducers and various on-board processes. Sensors are adopting various industrial automation protocols and getting smarter by being able to incorporate AI/DL technologies. There is a range of smart wireless SoCs available for single chip solutions with wireless and data processing functionalities. Auto calibration is another feature available in most of the signal conditioning chips. A leading semiconductor manufacturer recently announced a SoC which has a built-in signal conditioning unit specifically to handle multiple sensors and a CPU to process the process data. The CPU platform can be used to incorporate various industrial communication protocols. Sensor systems are trending to single chip low-power systems with Industrial protocol support, this will yield the Low cost high reliable sensor.
Jegajith P T, Embedded Practice Head, is Utthunga’s R&D manager of product development for various electronics and embedded systems. Throughout his career spanning 14+ years, he has led and coordinated teams of embedded system professionals in the development of software, firmware and integrated embedded systems and IoT devices. Jegajith is skilled in researching, evaluating and synthesising technical information to design system electronics, firmware and software. He is also a Machine Learning and Artificial Neural Network Architect, specialising in code optimisation for hardware deployment.