The Internet of Things (IoT) is all about making life simpler and more exciting for consumers by interconnecting the world around them. But how can this promise of the IoT be fulfilled?
In the world of IoT, microelectromechanical systems (MEMS) sensors form the backbone of the interface between the user and the multitudes of devices that surround us, such as smartphones, wearables, robots, and drones. However, making devices able to sense and be connected is simply not enough to realize the grand promise of the IoT.
The fact remains, that IoT will only be successful if it follows a user-centric approach, i.e. by solving real-life everyday challenges, making life simpler, enhancing ease of use. Furthermore, ubiquitous sensing of everything on all manner of devices in an ever-increasing number of complex environments poses definite and growing challenges for sensor providers. These challenges as well as the possible solutions to overcome them are discussed below from a sensor vendor’s perspective.
Three-Pronged Challenge For Smart Sensors In The IoT
When we consider today’s smart sensor modules, which contain certain processing capabilities integrated with the raw sensors, it boils down to three key challenges:
I. The first challenge is the technology itself. Vendors are pushed to leverage their core MEMS and system know-how to achieve the almost impossible. There are physical constraints challenging the engineer, package sizes cannot shrink forever, whilst demands for lower power and higher performance continue to rise incessantly.
Vendors are also forced to embed more and more intelligence and awareness into these systems. To achieve this aim, technology will need to be leveraged across multiple product platforms.
II. The second challenge results from the industry’s broad fragmentation. Today, the bulk of revenue booked from MEMS sensors comes from the smartphone segment, i.e., there are more than a billion smartphones sold each year with each containing at least one MEMS sensor. Here, the smartphone OEMs set the specifications and the vendors, such as Bosch Sensortec, define their MEMS sensors accordingly.
But the IoT world is very different, characterized by a highly fragmented structure of competing technological platforms. The demands placed on the sensor subsystem comprising of the sensors, microcontrollers and actuators vary widely across the IoT space. Therefore, vendors such as Bosch Sensortec need to create cross-platform solutions integrating hardware and software, and provide application-specific software. By leveraging software and expert application know-how, vendors help their customers to solve specific issues without having to tailor a custom hardware solution for each and every individual application.
III. The final challenge is geometrically expanding complexity. IoT systems are inherently complex, and OEMs often require turnkey solutions or reference designs. Bottom line, supplying just components is no longer enough.
Market-leading vendors meet these requirements head on with integrated smart sensor solutions, which greatly reduce complexity by incorporating increasingly more system processing power into single modular devices. And since no one company can provide an all-encompassing complete solution, suppliers must also closely co-operate and form partnerships with third parties, for example, in creating reference designs.
IoT Sensor Information Hierarchy
The IoT information structure is comprised of several levels, which, for a typical application, can be ranked in the following order of increasing information usefulness:
Sensor Information Hierarchy
- Raw data
- Motion detection
- Activity monitoring
- Context awareness
- Intent prediction
Although raw data may be filtered, compensated and corrected, in most cases there are definite limits to what a user can do with it. At the subsequent level, by identifying patterns and applying algorithms, data can be interpreted to provide motion detection information. Then, by adding in additional sensor functions, such as altitude detection through barometric pressure measurement, we go up another level to assign inferred activity monitoring information.
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