bullet Self-Adaptive Intelligent Sensors and Systems:
    From Theory to Practical Design



Sergey Y. Yurish


Keynote presentation at IEEE International Workshop on RObotic and Sensors Environments (ROSE' 2008)

17-18 October 2008, Ottawa, Canada, pp.X-XI





Intelligent sensors and sensor systems are of great interest in many fields of industry, control systems, robotics, biomedical applications, etc. According to new sensors market studies (Freedonia Group), the US sensor demand will grow 4.3 percent annually through 2012 and will reach $12.1 billion in 2010. It was marked also in a review (Frost & Sullivan) that ‘the past few decades have witnessed an explosive growth in sensors and sensor-based applications which has led to a greater demand for sensor interfacing integrated circuits (ICs)’. According to Frost & Sullivan the forecast for North American smart sensors market is to reach $635.2 million in 2010. Strong growth expected for sensors based on MEMS-technologies, smart sensors and sensors with bus capabilities.


Nowadays, intelligent sensors and systems are extremely necessary for such applications, as electronic noses and tongues, smart vision systems, personnel (human body) detection, authentication systems, building monitoring system, etc. Most effectively for achievement of this purpose is a combination of technological methods and structural-algorithmic methods in order to improve metrological performance of digital and intelligent sensors and sensor systems. It allows to achieve the same performances (or even better) at reduced material and human costs, with a much faster response.


The modern definition of smart or intelligent sensors can be formulated now by the following way: ‘Smart sensor is an electronic device, including sensing element, interfacing, signal processing and one- or several intelligence functions as self-testing, self-identification, self-validation or self-adaptation’. The keyword in this definition is ‘intelligence’. The self-adaptation is a relatively new function of smart sensors and sensor systems. Self-adaptation smart sensors and systems are based on so-called adaptive algorithms and directly connected with precision measurements of frequency-time parameters of electrical signals.


Recent developments in the field of smart sensors design, novel adaptive algorithms and practical examples of its realizations in various self-adaptive smart sensors and sensor systems with parametric adaptation are described in this presentation. The adaptive algorithms are based on novel advanced methods of measurements such as modified method of the dependent count with programmable relative error and non-redundant time of measurement, and the method with non-redundant reference frequency. Equations of measurements for these methods are given and decision rules formulated. Some practical examples of self-adaptive smart sensor systems based on the Universal Frequency-to-Digital Converter (UFDC), Universal Sensors and Transducers Interface (USTI) integrated circuits, and ultra-low-power microcontroller are outlined in the presentation. The presentation is illustrated by examples and presents an alternative to the classical approach to data acquisition and covers signal processing methods for quasi-digital sensors with frequency (period), duty-cycle or pulse width modulated output.


In addition to the self-adaptation function, the self-identification function of smart sensors according to the IEEE 1451 standard will be also discussed. The simple extension of IEEE 1451 standards family for quasi-digital sensors with frequency (period), duty-cycle and pulse width modulated outputs will provide smart transducer manufactures with the ability to produce quickly and with low-cost different IEEE 1451 compatible sensors, transducers, measuring and data acquisition systems. The approach needs also only one of universal component - the USTI (or UFDC-2) chip, which covers three main functions of smart transducers: high accurate frequency (time)-to-digital conversion, TEDS storage in the flash memory and communications. Such chips can be embedded into any existing frequency-time domain output sensors or transducers (with the help of integrated or hybrid technologies) to produce IEEE 1451.4 compatible sensors as well as into IEEE 1451.4 compatible data acquisition systems. Due to all these, smart transducer manufactures will receive 15Έ20 % of addition global sensors market, which was not involved before into the IEEE 1451 standardization process.


Design and development of IEEE 1451 compatible sensors and transducers will be quick, low-cost and effective. Such approach will improve the level of commercial adoption of IEEE 1451 standards family in industry.


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