Today, sensors play a vital role in detecting diverse parameters that benefit multiple sectors and industries. With the widespread adoption of the Internet of Things (IoT), both these sensors and their supporting hardware are managed and connected within an intelligent digital network.
In this context, we synthesized a consulting report highlighting key technological trends and innovation opportunities in sensing and automation for 2021. The report focuses on five core thematic areas outlined below.
Connected Living
Sensors now enable remote patient health monitoring as well as the control of smart home appliances and entertainment systems, among many other applications. Internet-connected smartphones and home devices generate massive volumes of data, which artificial intelligence (AI) leverages to draw inferences and predict impending events.
Sensor fusion uses algorithms to combine data from multiple sources (such as LiDAR and smart sensors) to map environments with higher accuracy. Key application areas include the automotive industry, consumer electronics, defense and military, and healthcare. For instance, this approach is set to elevate Advanced Driver Assistance Systems (ADAS) and Highly Automated Driving (HAD) to new performance levels.
Autonomous Vehicles
The report indicates that ADAS systems—which alert drivers to potential hazards—will power the autonomous vehicles of tomorrow. These technologies deliver greater safety and promise to significantly reduce accident rates. Technologies including Light Detection and Ranging (LiDAR) sensors, radar sensors, CMOS, infrared, ultrasonic sensors, and 3D vision camera systems enable a vehicle to gather real-time spatial data, anticipate obstacles, and alert the driver.
Furthermore, the convergence of ADAS technologies with autonomous vehicles will unlock disruptive mobility services, including driverless taxis, trucks, buses, and automated delivery fleets.
Machine-to-Machine Sensors
The Industrial Internet of Things (IIoT) and Industry 4.0 rely on machine-to-machine (M2M) communication and connectivity. This framework allows devices to exchange data bi-directionally, streamlining decision-making and automated action plans. This connectivity can extend beyond the shop floor to encompass external partners, remote facilities, or off-site personnel.
Within smart factories, sensors detect objects, monitor operational processes, track finished goods, and evaluate environmental conditions. This capabilities stack enables richer data sharing, deeper connectivity, higher levels of automation, and mass customization.
These advancements also extend to other sectors, such as agriculture, which increasingly relies on soil sensors, sensor networks, and drone-based aerial monitoring.
Cobotic Transformation
Driven by Industry 4.0 and smart manufacturing, the industrial sector has prioritized the development and adoption of advanced automation solutions. This shift created major opportunities for collaborative robots (cobots), which work safely alongside humans in environments like logistics warehouses to boost operational efficiency.
Digitalization and Automation
In manufacturing, real-time analytical solutions will play a central role in driving efficiency and reducing system downtime. Meanwhile, cognitive manufacturing—incorporating technologies such as machine learning, deep learning, voice and pattern recognition, natural language processing, and computer vision—will redefine human-machine interaction in industrial environments.
To dive deeper into this topic, we invite you to read the full report.