See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/3090944 Sensor technology advances and future trends Article in IEEE Transactions on Instrumentation and Measurement · January 2005 DOI: 10.1109/TIM.2004.834613 · Source: IEEE Xplore CITATIONS READS 46 14,887 2 authors, including: Olfa Kanoun Technische Universität Chemnitz 444 PUBLICATIONS 1,340 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: MWCNT-PDMS pressure sensors View project Image postprocessing with decision trees of reconstructed Images of electrical impedance tomography reconstructed with EIDORS View project All content following this page was uploaded by Olfa Kanoun on 18 February 2014. The user has requested enhancement of the downloaded file. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 53, NO. 6, DECEMBER 2004 1497 Sensor Technology Advances and Future Trends Olfa Kanoun and Hans-Rolf Tränkler Abstract—Recent advances of sensor technologies have been powered by high-speed and low-cost electronic circuits, novel signal processing methods, and advanced manufacturing technologies. The synergetic interaction of new developments in these fields provides promising technical solutions increasing the quality, reliability, and economic efficiency of technical products. With selected examples, we will give an overview about the significant developments of methods, structures, manufacturing technologies, and signal processing characterizing today’s sensors and sensor systems. Predominantly observed development trends in the future are discussed. Index Terms—Future trends, review, sensor signal processing, sensor technology, smart sensors. Fig. 1. Decisive fields for the development of sensor technology. I. INTRODUCTION T HE COMPETITION in markets requires the permanent enhancement of quality and reliability of products. The rising demand for automation, security, and comfort leads to completely new applications for sensor systems. The number of sensor systems required and the diversity in most applications are permanently increasing. To keep up with the new requirements, the design of sensor systems is required to provide novel approaches and solutions profiting from recent developments in science and technology. Sensors and sensor systems achieve their function through an interlocked interaction of sensor structure, manufacturing technology, and signal processing algorithms. The developments in sensor technology are consequently based on the permanent technical progress in these fields (Fig. 1). Particularly, in the last years, a significant upturn is observed in these fields involving a great potential for completely novel approaches of sensors and sensor systems. Using new technologies and signal processing methods, even well-known measurement principles could be used, leading to considerably improved sensor features. II. SENSOR STRUCTURE In the kernel of a sensor system is the sensor element, which changes its output depending on the measured quantity. In a preprocessing unit, the sensor signal is transformed in an adequate amplified and filtered signal using analog signal processing techniques. Using digital signal processing, the measured quantity can be calculated under consideration of manufacturing variance, influence factors, and aging processes . Manuscript received June 15, 2003; revised March 24, 2004. The authors are with the Institut für Meß- und Automatisierungstechnik, University of the Bundeswehr Munich, Neubiberg, Germany (e-mail: [email protected]). Digital Object Identifier 10.1109/TIM.2004.834613 By means of low-cost analog-to-digital converters, signal processing is increasingly shifted from the higher system level in the sensor level. The diverse facilities in digital signal processing involve new approaches for the improvement of sensor properties. Calibration and consideration of several effects, such as manufacturing variance or cross sensitivity, become a simple task. Embedding other functions, such as online self-test or selfcalibration, is today winning a special importance, improving the system reliability, and reducing installation and maintenance costs. The structure of a sensor with self-monitoring differs from the standard structure in particular through the consideration of supplementary knowledge to the actual measurement information. Generally, specific relationships are required about the sensor behavior and the expected confidence limits of sensor properties . The state of the sensor system can be inspected by a comparison of the real output to the expected value due to the previously known relationships . For instance, acceleration sensors with a closed-loop structure compensate the inertial force acting on the mass through an electrically generated restoring force (Fig. 2). Through the application of restoring forces with well-known values, self-tests can be carried out . For a self-calibration process, the real sensor outputs by fixed well-known inputs are moreover used in order to calculate sensor parameters. Through self-calibration, aging effects can be compensated so that defined measurement accuracy limits could be guaranteed during the whole operating time. The trend toward built-in self-test or self-calibration function leads to the design of totally calibration-free sensor systems. In recent research dealing with temperature measurement based on p-n junctions , a novel sensor principle has been developed, in which temperature can be calculated without needing any calibrations during production or maintenance processes. 0018-9456/04$20.00 © 2004 IEEE 1498 IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 53, NO. 6, DECEMBER 2004 The a priori knowledge about the sensor behavior is represented in this case by the model of the – characteristic. Temperature is one unknown parameter, among others (Fig. 3). The measured voltages at different supply currents are fitted to the – characteristic model, so that temperature is simultaneously calculated online together with all unknown parameters in the characteristic model. III. SENSOR TECHNOLOGY Many recent advances in the sensor technology become mainly possible by means of micro technologies. These new technologies offer high-volume manufacturable systems with small dimensions, lower power consumption, and higher reliability. Thereby, realized microsystems integrate sensors, actuators, mechanical, and electronic units. They provide low-cost solutions that were not realizable with microelectronic systems. Their development involves special challenges for device modeling, microfabrication, material, and packaging technologies. Micromachined systems are today already inherent components in automotives, color printers, mobile phones, and medical systems. The most popular micromachined sensors are pressure, angular rate (Fig. 4), and acceleration sensors. They allowed the widespread implementation of low-cost airbag systems and catalytic converters. Silicon micromachining is one of the most significant micro technologies for sensor systems . The eminent properties of the silicon material, such as the freedom of hysteresis errors, and the earlier advances in the field of microelectronics have permitted this important technical evolution. In case of bulk micromachining, the substrate is structured by means of wet and dry etching processes. The high etching selectivity and reliability are the advantages of the bulk micromachining . In an isotropic process, the etching speed is independent from the direction in the substrate. In this case, the obtainable device configurations are limited and the silicon material may not be efficiently utilized. In an anisotropic process, the etching speed is orientation dependent. The manufactured structures in bulk micromachining have from the beginning a high aspect ratio. This means that the structure height is high relative to the minimal lateral dimension of the whole structure. This property involves considerable advantages for sensor performance, such as higher sensitivity, displacement, mechanical robustness, and reduced noise. In case of surface micromachining, three-dimensional mechanical structures are developed by a sequential deposition and selectively removing of sacrificial layers (e.g., SiO ) separating the individual layers in the structure. Recently, the use of reactive ion etching (RIE) allowed a cost-effective realization of structures with a higher aspect ratio of 30 . IV. SIGNAL PROCESSING The signal processing has the task of determining the measured quantity from the measured data in spite of all unavoidable effects, such as manufacturing variance, influence factors, and aging processes, which represent an additional source of systematical measurements errors. Fig. 2. Acceleration sensor with a closed-loop structure. Fig. 3. Calibration-free temperature measurement based on the p-n junction I –U characteristic . Fig. 4. Angular rate sensor in surface micromachining . A. Signal Processing for Individual Sensors Whereas the sensor element can deliver a weak signal, the transmitted signal should generally have a high signal level, and perhaps suitable values, in order to reach superior units undisturbed and to simplify the following calculations. Therefore, the sensor signal should be generally preprocessed. Thereby several important tasks could be realized (Fig. 5), such as signal amplification, scaling, linearization, conversion, and conjunctions with other components in a chain, parallel, or closed-loop structure . For instance, giant magnetoresistance (GMR) elements are able to measure an angle with a high resolution . A particular property of these elements is that they can measure the direction of a magnetic field independently of its amplitude. In this KANOUN AND TRÄNKLER: SENSOR TECHNOLOGY ADVANCES AND FUTURE TRENDS Fig. 5. Signal processing by individual sensors. case, the sensor signal must be generally amplified and the temperature influence compensated. The actual calculation of the angle is carried out by an analog signal processing in a half or a full bridge circuit with GMR elements with different preference magnetization. Today, a current practice is the local digitalization of the sensor signal. In addition to the disburden of the higher system, the local signal digitalization has the advantage, that measurement data could be transmitted without remarkable precision loss independently of the distance between the sensor and the higher processing unit. The signal processing is increasingly shifted from hardware to software, so that measurement accuracy can be simpler improved. Manufacturing variances can be considered by a simple parameterization instead of mechanical or electrical trimming processes. Physical or mathematical models describing the sensor behavior can be used, taking into account influence effects and realizing a more precise measurement. The possibility to use sophisticated signal processing methods leads to completely new sensors using principles, which are in fact already well known. However, technological problems, such as manufacturing variance, or the low level of the signal, prevented their effective use for measurements. 1499 vide synergetic effects that enhance the quality and availability of information about the state of the measurement environment. The aim of the signal processing by multisensor systems is to acquire determined information, such as a decision or the measurement of a quantity, using a selected set of measured data stemming from a multisensor system. Generally, a certain level of precision or reliability is required that only one sensor could not achieve. For example, for presence detection, ultrasonic detectors have a high sensitivity to noise, thermal-induced air turbulence, and movements of hanging curtains and plants. Microwave detectors can also be used for presence detection, but they may detect an object motion outside the observed room or be misled by other electromagnetic fields (mobile telephones, etc.). The combination of both detectors and the use of adapted signal processing  achieve a better detection reliability because of the different ways in which both detectors are affected by disturbances. Sophisticated signal processing based on data fusion techniques can generally improve the measurement accuracy more than the more common simple threshold-based algorithms. The process of multisensor data fusion should be specially designed in each case under consideration of the special circumstances in the target application in order to ensure the right calculation of the required measurement values or decisions. For instance, the use of several low cost sensors in a multisensor system can reach a significant improvement of reliability and precision in the gas concentration measurement . Important circumstances for the data fusion are, in this case, the cross sensitivity of the sensors and effects of influence factors such as temperature, humidity, or pressure. Separate sensors should generally measure the relevant influence factors. Through calibration processes, the reaction of the multisensor system on different lead gases is tested. Depending on the sensor reaction, the combination of sensors for data fusion is determined. An accurate concentration measurement can, thereby, be carried out in spite of the deficiencies of the individual sensors . Multisensor systems are today indispensable in hazard warning applications such as free-range protection by video signal evaluation, detection of lying persons, or in the early fire detection, because of the required high level of reliability. For instance, in the early fire detection, sensor arrays, including optical scattered light detectors and gas sensors, have been proposed . In this case, the signal processing should be able to discriminate between fire, not-fire, and disturbing event situations by identifying fire signatures from measured sensor responses  (Fig. 6). A feature extraction unit is required in order to reduce the dimensionality of the measurement space and to extract suitable information characterizing fire situations. The extracted features are then classified by means of a neural network in order to estimate the class to which the measured data belong and to know if an alarm should be sent to the fire brigade. B. Signal Processing for Multisensor Systems In general, single sensor systems can only provide partial information on the state of the environment, while multisensor systems combine related data from multiple similar and/or different sensors. The goal of using multisensor systems is to pro- V. FUTURE TRENDS IN SENSOR TECHNOLOGY The development trends in sensor technology result from market-economical aspects, general customer requests, and specific requirements of the target applications. 1500 Fig. 6. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 53, NO. 6, DECEMBER 2004 Structure of a sophisticated fire detection algorithm . Costs reductions and more improvement in accuracy and speed will be achieved in the future using measurement methods with higher performance, new manufacturing technologies, and sophisticated signal processing methods. The greater demand for environmental protection demands the development of highly reliable sensors. Maintenance-free sensors with long life expectancy and low electric power consumption will, thereby, be the focus of interests. The main development trends in sensor technology are, in general, toward miniaturization and an increasing use of multisensor and wireless systems (Fig. 7). A. Trend in Miniaturization: Microsystem Technology Miniaturization is an outstanding strategy of success in modern technologies. A reduction of characteristic dimensions usually results in shorter response times so that a correspondingly higher speed is achievable in signal generation and processing. In many cases, it reduces costs because of the higher integration rate, lower power consumption, and higher reliability. Miniaturization is generally gaining importance in all fields of applications, where smaller structures and greater precision are becoming decisive to the market acceptance of individual products. The development trend to miniaturization goes on within nanotechnologies, which will open up access to still smaller dimensions . For instance, for the monitoring of vital parameters of human beings, health care devices can be used so that an emergency call could be released automatically in case of unconsciousness of the observed person. For acceptance by users, the device should be light and provide unhindered mobility. The user should be able to ignore it and to live normally without being obliged to take it off in any situation during the whole day. The concept of the MIT-ring (Fig. 8), as a highly miniaturized solution, fulfills the requirements for this special application. A light-emitting diode in the ring continuously emits light into the finger of the observed person. By an evaluation of the reflected light, the ring can measure the pulse rate, the potential cardiac condition, and possibly blood pressure. By means of an embedded antenna, signals can be transmitted to a signal receiver nearby. B. Trend in the Use of Multisensors The use of multisensor systems is becoming more important in widespread applications –. Their applications reach from the monitoring and automation of manufacturing processes to robotics, automotive applications, smart home, Fig. 7. Future trends in sensor technology. Fig. 8. MIT-ring for healthcare . process control, environmental engineering, biotechnology, and life sciences. Multisensor systems provide the advantage that economical sensors can be used even for the achievement of a high level of precision and reliability. Thereby, a big amount of available information is managed using sophisticated signal processing techniques so that the system achieves a better performance. Multisensor data fusion is in effect intrinsically performed by animals and human beings to achieve a more accurate assessment of the surrounding environment . A directly related example is the electronic nose, which consists of an array of different sensors that have been shown to respond to definite organic and inorganic compounds with low concentrations. In order to reach a high resolution at low concentrations, the response of a sensor array is used like in the real human nose. The applications of the electronic nose are widespread in the chemical analysis, environment monitoring, food and wine inspection, emission control, and narcotic detection. The development trends of multisensor systems are in the development of modular systems , which are easily extendible with new units without disturbing the already available functions. C. Trend in Wireless Systems With the large amount of components, which are indispensable for the achievement of the required functionality, the electric wiring of spatially distributed systems becomes complex and causes difficulties in the system’s handling. The use of wireless systems implies a better convenience and leads to a considerable cost reduction. Wireless sensor systems have the advantage that they can be placed anywhere, and can, KANOUN AND TRÄNKLER: SENSOR TECHNOLOGY ADVANCES AND FUTURE TRENDS therefore, record the measured quantity closely to its occurrence, independent of potential harsh circumstances. Wireless sensors can communicate over ultrasonic or infrared signals , . For instance, surface acoustic wave devices (SAW transponders)  can be used for object identification and for the measurement of physical, chemical, and biological quantities such as temperature, pressure, torque, acceleration, or humidity. Energy-autonomous sensors will gain a particular importance among wireless sensors  because, in this case, wires are no longer necessary, even for electricity supply. This kind of sensor is necessary for many applications in which long distances are to be bridged, or a large number of distributed components are necessary. VI. CONCLUSION Sensor technology profits from synergetic concurrence of both manufacturing technologies and signal processing methods. New sensors provide promising technical solutions, which can significantly contribute to an improvement of quality, reliability, and economic efficiency of technical products. For the development of new sensors, an interdisciplinary work of key competence from university and industry is indispensable. In the future, sensor systems would be designed in an integrated design process, including not only the technological aspects, but also the design of the specific manufacturing steps and signal processing algorithms. 1501  D. R. Sparks, S.-C. Chang, and D. S. Eddy, “Applications of MEMS technology in automotive sensors and actuators,” in Proc. Int. Symp. Micromechatronics Human Sci., Nov. 25–28, 1998.  K.-M. H. Lenssen, D. J. Adelerhof, H. J. Gassen, A. E. T. Kuiper, G. H. J. Somers, and J. B. A. van Zon, “Robust giant magnetoresistance sensors,” in Proc. Eurosensors XIII, The Hague, The Netherlands, Sept. 12–15, 1999, pp. 589–596.  H. Ruser, A. v. Jena, V. Mágori, and H.-R Tränkler, “A low-cost ultrasonic-microwave multisensor for robust sensing of velocity and range,” presented at the Proc. Sensor., Nürnberg, Germany, 1999.  T. Doll, I. Eisele, and H.-R. Tränkler, Intelligentes Gas-Multisensorsystem. Rosenheim: Geronimo-Verlag, 1998.  F. Derbel, “Performance improvement of fire detection systems by means of gas sensors and LVQ neural networks,” presented at the Proc. ACIDCA., Monastir, Tunisia, 2000.  S. D. Senturia, “Simulation and design of microsystems: A 10 year perspective,” Sens. Actuators, vol. A 67, pp. 1–7, 1998.  E. A. Thomson, H. H. Asada, and B.-H. Yang, MIT Ring Monitors Patients’ Vital Signs. Cambridge, MA: MIT News, 1997.  W.-E. Bulst, G. Fischerauer, and L. Reindl, “State of the art in wireless sensing with surface acoustic waves,” IEEE Trans. Ind. Electron., vol. 48, pp. 265–271, Apr. 2001. Olfa Kanoun was born in Sfax, Tunisia, in 1970. She received the M.Sc. degree from the Technical University in Munich, Germany, in 1995 and the Ph.D. degree on calibration-free temperature measurement using p-n junctions from the Institute for Measurement and Automation, University of Bundeswehr Munich, Neubiberg, Germany, in 2001, where she is currently pursuing the habilitation degree in the field of smart sensors. Dr. Kanoun was awarded for best dissertation in 2001 by the AHMT (The Commission of Professors in Measurement Technology in Germany). REFERENCES  H.-R. Tränkler and O. Kanoun, “Symbiosis of information and sensor technologies,” in Proc. Sensors, Nürnberg, Germany, May 13–15, 2003.  G. Schneider, “Status monitoring and selfcalibration of sensors,” Automatisierungstechnische Praxis, vol. 38, no. 9, pp. 9–17, 1996.  O. Kanoun, “Modeling the P-N junction I –U characteristic for an accurate calibration-free temperature measurement,” IEEE Trans. Instrum. Meas., vol. 49, pp. 901–905, Aug. 2000.  M. Esashi, “Microsystems by bulk micromachining,” in Proc. 30th European Microwave Conf., vol. 1, 2000, pp. 248–251.  H.-P. Trah and R. Neul, “Physik und Design micromechanischer Automobilsensoren,” VDI-Berichte, Ludwigsburg, Germany, Rep. 1530, 2000. View publication stats Hans-Rolf Tränkler was born in Munich, Germany, in 1941. Since 1980, he has been a University Professor at the Institute for Measurement and Automation, The University of Bundeswehr Munich, Neubiberg, Germany. He is the head of this institute where he has been leading different research projects in several fields in instrumentation and measurement. His recent research projects have dealt with investigation and modeling of sensors for physical and chemical quantities, smart sensor systems, and sensor actuator systems for smart home applications.