Dependability assessment of by-wire control systems using fault injection

This paper is focused on the validation by means of physical fault injection at pin-level of a time-triggered communication controller: the TTP/C versions C1 and C2. The controller is a commercial off-the-shelf product used in the design of by-wire systems. Drive-by-wire and fly-by-wire active safety controls aim to prevent accidents. They are considered to be of critical importance because a serious situation may directly affect user safety. Therefore, dependability assessment is vital in their design. This work was funded by the European project `Fault Injection for TTA¿ and it is divided into two parts. In the first part, there is a verification of the dependability specifications of the TTP communication protocol, based on TTA, in the presence of faults directly induced in communication lines. The second part contains a validation and improvement proposal for the architecture in case of data errors. Such errors are due to faults that occurred during writing (or reading) actions on memory or during data storage.Blanc Clavero, S.; Bonastre Pina, AM.; Gil, P. (2009). Dependability assessment of by-wire control systems using fault injection. Journal of Systems Architecture. 55(2):102-113. doi:10.1016/j.sysarc.2008.09.003S10211355

A New Ammonium Smart Sensor with Interference Rejection

[EN] In many water samples, it is important to determine the ammonium concentration in order to obtain an overall picture of the environmental impact of pollutants and human actions, as well as to detect the stage of eutrophization. Ion selective electrodes (ISEs) have been commonly utilized for this purpose, although the presence of interfering ions (potassium and sodium in the case of NH4+-ISE) represents a handicap in terms of the measurement quality. Furthermore, random malfunctions may give rise to incorrect measurements. Bearing all of that in mind, a smart ammonium sensor with enhanced features has been developed and tested in water samples, as demonstrated and commented on in detail following the presentation of the complete set of experimental measurements that have been successfully carried out. This has been achieved through the implementation of an expert system that supervises a set of ISEs in order to (a) avoid random failures and (b) reject interferences. Our approach may also be suitable for in-line monitoring of the water quality through the implementation of wireless sensor networks.This research was supported by the Spanish Ministerio de Economia y Competitividad, grant number DPI2016-80303-C2-1-P.Capella Hernández, JV.; Bonastre Pina, AM.; Campelo Rivadulla, JC.; Ors Carot, R.; Peris Tortajada, M. (2020). A New Ammonium Smart Sensor with Interference Rejection. Sensors. 20(24):1-17. https://doi.org/10.3390/s20247102S1172024Molins-Legua, C., Meseguer-Lloret, S., Moliner-Martinez, Y., & Campíns-Falcó, P. (2006). A guide for selecting the most appropriate method for ammonium determination in water analysis. TrAC Trends in Analytical Chemistry, 25(3), 282-290. doi:10.1016/j.trac.2005.12.002Zhu, Y., Chen, J., Yuan, D., Yang, Z., Shi, X., Li, H., … Ran, L. (2019). Development of analytical methods for ammonium determination in seawater over the last two decades. TrAC Trends in Analytical Chemistry, 119, 115627. doi:10.1016/j.trac.2019.115627Liu, J. (2020). New directions in sensor technology. TrAC Trends in Analytical Chemistry, 124, 115818. doi:10.1016/j.trac.2020.115818Yaroshenko, I., Kirsanov, D., Marjanovic, M., Lieberzeit, P. A., Korostynska, O., Mason, A., … Legin, A. (2020). Real-Time Water Quality Monitoring with Chemical Sensors. Sensors, 20(12), 3432. doi:10.3390/s20123432Martı́nez-Máñez, R., Soto, J., Garcia-Breijo, E., Gil, L., Ibáñez, J., & Llobet, E. (2005). An «electronic tongue» design for the qualitative analysis of natural waters. Sensors and Actuators B: Chemical, 104(2), 302-307. doi:10.1016/j.snb.2004.05.022Legin, A. ., Rudnitskaya, A. ., Vlasov, Y. ., Di Natale, C., & D’Amico, A. (1999). The features of the electronic tongue in comparison with the characteristics of the discrete ion-selective sensors. Sensors and Actuators B: Chemical, 58(1-3), 464-468. doi:10.1016/s0925-4005(99)00127-6Mueller, A. V., & Hemond, H. F. (2013). Extended artificial neural networks: Incorporation of a priori chemical knowledge enables use of ion selective electrodes for in-situ measurement of ions at environmentally relevant levels. Talanta, 117, 112-118. doi:10.1016/j.talanta.2013.08.045Wen, Y., Mao, Y., Kang, Z., & Luo, Q. (2019). Application of an ammonium ion-selective electrode for the real-time measurement of ammonia nitrogen based on pH and temperature compensation. Measurement, 137, 98-101. doi:10.1016/j.measurement.2019.01.031Handbook of Electrochemistry. (2007). doi:10.1016/b978-0-444-51958-0.x5000-9Umezawa, Y., Bühlmann, P., Umezawa, K., Tohda, K., & Amemiya, S. (2000). Potentiometric Selectivity Coefficients of Ion-Selective Electrodes. Part I. Inorganic Cations (Technical Report). Pure and Applied Chemistry, 72(10), 1851-2082. doi:10.1351/pac200072101851Capella, J. V., Bonastre, A., Ors, R., & Peris, M. (2015). An interference-tolerant nitrate smart sensor for Wireless Sensor Network applications. Sensors and Actuators B: Chemical, 213, 534-540. doi:10.1016/j.snb.2015.02.125Choudhary, J., Balasubramanian, P., Varghese, D., Singh, D., & Maskell, D. (2019). Generalized Majority Voter Design Method for N-Modular Redundant Systems Used in Mission- and Safety-Critical Applications. Computers, 8(1), 10. doi:10.3390/computers8010010Capella, J. V., Bonastre, A., Ors, R., & Peris, M. (2014). A step forward in the in-line river monitoring of nitrate by means of a wireless sensor network. Sensors and Actuators B: Chemical, 195, 396-403. doi:10.1016/j.snb.2014.01.039Cuartero, M., Colozza, N., Fernández-Pérez, B. M., & Crespo, G. A. (2020). Why ammonium detection is particularly challenging but insightful with ionophore-based potentiometric sensors – an overview of the progress in the last 20 years. The Analyst, 145(9), 3188-3210. doi:10.1039/d0an00327aBembe, M., Abu-Mahfouz, A., Masonta, M., & Ngqondi, T. (2019). A survey on low-power wide area networks for IoT applications. Telecommunication Systems, 71(2), 249-274. doi:10.1007/s11235-019-00557-9Freiser, H. (Ed.). (1980). Ion-Selective Electrodes in Analytical Chemistry. doi:10.1007/978-1-4684-3776-8Peris, M., Bonastre, A., & Ors, R. (1998). Distributed expert system for the monitoring and control of chemical processes. Laboratory Robotics and Automation, 10(3), 163-168. doi:10.1002/(sici)1098-2728(1998)10:33.0.co;2-2Carminati, M., Turolla, A., Mezzera, L., Di Mauro, M., Tizzoni, M., Pani, G., … Antonelli, M. (2020). A Self-Powered Wireless Water Quality Sensing Network Enabling Smart Monitoring of Biological and Chemical Stability in Supply Systems. Sensors, 20(4), 1125. doi:10.3390/s20041125Nakas, C., Kandris, D., & Visvardis, G. (2020). Energy Efficient Routing in Wireless Sensor Networks: A Comprehensive Survey. Algorithms, 13(3), 72. doi:10.3390/a13030072Capella, J. V., Bonastre, A., Campelo, J. C., Ors, R., & Peris, M. (2020). IoT & environmental analytical chemistry: Towards a profitable symbiosis. Trends in Environmental Analytical Chemistry, 27, e00095. doi:10.1016/j.teac.2020.e00095Pretsch, E. (2007). The new wave of ion-selective electrodes. TrAC Trends in Analytical Chemistry, 26(1), 46-51. doi:10.1016/j.trac.2006.10.006STM Microelectronics https://www.st.com/content/st_com/en/products/microcontrollers-microprocessors/stm32-32-bit-arm-cortex-mcus/stm32-ultra-low-power-mcus/stm32l4-series/stm32l4x2/stm32l422cb.htmlAnalog Devices https://www.analog.com/media/en/technical-documentation/data-sheets/AD524.pdfCapella, J. V., Bonastre, A., Ors, R., & Peris, M. (2010). A Wireless Sensor Network approach for distributed in-line chemical analysis of water. Talanta, 80(5), 1789-1798. doi:10.1016/j.talanta.2009.10.025Bonastre, A., Capella, J. V., Ors, R., & Peris, M. (2012). In-line monitoring of chemical-analysis processes using Wireless Sensor Networks. TrAC Trends in Analytical Chemistry, 34, 111-125. doi:10.1016/j.trac.2011.11.009Mei-Chen Hsueh, Tsai, T. K., & Iyer, R. K. (1997). Fault injection techniques and tools. Computer, 30(4), 75-82. doi:10.1109/2.58515

IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water.

[EN] The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.FundingThis research was funded by Spanish Ministerio de Economia y Competitividad, Gobierno de Espana, grant number DPI2016-80303-C2-1-P.Campelo Rivadulla, JC.; Capella Hernández, JV.; Ors Carot, R.; Peris Tortajada, M.; Bonastre Pina, AM. (2022). IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water. Sensors. 22(3):1-16. https://doi.org/10.3390/s2203084211622

New Contact Sensorization Smart System for IoT e-Health Applications Based on IBC IEEE 802.15.6 Communications

[EN] This paper proposes and demonstrates the capabilities of a new sensorization system that monitors skin contact between two persons. Based on the intrabody communication standard (802.15.6), the new system allows for interbody communication, through the transmission of messages between di erent persons through the skin when they are touching. The system not only detects if there has been contact between two persons but, as a novelty, is also able to identify the elements that have been in contact. This sensor will be applied to analyze and monitor good follow-up of hand hygiene practice in health care, following the ¿World Health Organization Guidelines on Hand Hygiene in Health Care¿. This guide proposes specific recommendations to improve hygiene practices and reduce the transmission of pathogenic microorganisms between patients and health-care workers (HCW). The transmission of nosocomial infections due to improper hand hygiene could be reduced with the aid of a monitoring system that would prevent HCWs from violating the protocol. The cutting-edge sensor proposed in this paper is a crucial innovation for the development of this automated hand hygiene monitoring system (AHHMS).This research was funded by the Spanish Ministerio de Economia y Competitividad, grant number DPI2016-80303-C2-1-P.Hernández, D.; Ors Carot, R.; Capella Hernández, JV.; Bonastre Pina, AM.; Campelo Rivadulla, JC. (2020). New Contact Sensorization Smart System for IoT e-Health Applications Based on IBC IEEE 802.15.6 Communications. Sensors. 20(24):1-17. https://doi.org/10.3390/s20247097S117202

HMP: A Hybrid Monitoring Platform for Wireless Sensor Networks Evaluation

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Wireless sensor networks (WSNs), as an essential part of the deployment of the Internet of Things paradigm, require an adequate debugging and monitoring procedures to avoid errors in their operation. One of the best tools for WSN supervision is the so-called Monitoring Platforms that harvest information about the WSN operation in order to detect errors and evaluate performance. Monitoring platforms for the WSN can be hardware or software implemented, and, additionally, they can work in active or passive mode. Each approach has advantages and drawbacks. To benefit from their advantages and compensate their limitations, hybrid platforms combine different approaches. However, very few hybrid tools, with many restrictions, have been proposed. Most of them are designed for a specific implementation of WSN nodes; many of them are lack of a real implementation, and none of them provides an accurate solution to synchronization issues. This paper presents a hybrid monitoring platform for WSN, called HMP. This platform combines both hardware and software, active and passive monitoring approaches. This hybridization provides many interesting capabilities; HMP harvests the information both actively (directly from the sensor nodes) and passively (by means of messages captured from the WSN), causing a very low intrusion in the observed network. In addition, HMP is reusable; it may be applied to almost any WSN and includes a suitable trace synchronism procedure. Finally, HMP follows an open architecture that allows interoperability and layered development.This work was supported by the Agencia Estatal de Investigacion from the Spanish Ministerio de Economia, Industria y Competitividad, through the project Hacia el hospital inteligente: Investigacion en el diseno de una plataforma basada en Internet de las Cosas y su aplicacion en la mejora del cumplimiento de higiene de manos, under Grant DPI2016-80303-C2-1-P. The project covers the costs of publishing in open access.Navia-Mendoza, MR.; Campelo Rivadulla, JC.; Bonastre Pina, AM.; Capella Hernández, JV.; Ors Carot, R. (2019). HMP: A Hybrid Monitoring Platform for Wireless Sensor Networks Evaluation. IEEE Access. 7:87027-87041. https://doi.org/10.1109/ACCESS.2019.2925299S8702787041

El proyecto SimBioTIC de Llíria, apostando por la sostenibilidad

Bonastre Pina, AM.; Lemus Zúñiga, LG.; Oliver Villanueva, JV.; Urchueguía Schölzel, JF. (2017). El proyecto SimBioTIC de Llíria, apostando por la sostenibilidad. Retema Medio Ambiente. (203):94-99. http://hdl.handle.net/10251/104014S949920

Monitoring pest insect traps by means of low-power image sensor technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.). © 2012 by the authors; licensee MDPI, Basel, Switzerland.This work was partially funded by Ministry of Education and Science grants CTM2011-29691-C02-01, TIN2011-28435-C03-01 and TIN2011-27543-C03-03.López ., O.; Martinez Rach, MO.; Migallon ., H.; Pérez Malumbres, MJ.; Bonastre Pina, AM.; Serrano Martín, JJ. (2012). Monitoring pest insect traps by means of low-power image sensor technologies. Sensors. 12(11):15801-15819. doi:10.3390/s121115801S15801158191211Shelton, A. M., & Badenes-Perez, F. R. (2006). CONCEPTS AND APPLICATIONS OF TRAP CROPPING IN PEST MANAGEMENT. Annual Review of Entomology, 51(1), 285-308. doi:10.1146/annurev.ento.51.110104.150959Jiang, J.-A., Tseng, C.-L., Lu, F.-M., Yang, E.-C., Wu, Z.-S., Chen, C.-P., … Liao, C.-S. (2008). A GSM-based remote wireless automatic monitoring system for field information: A case study for ecological monitoring of the oriental fruit fly, Bactrocera dorsalis (Hendel). Computers and Electronics in Agriculture, 62(2), 243-259. doi:10.1016/j.compag.2008.01.005http://www.memsic.comAl-Saqer. (2011). Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition by Image Processing Techniques. American Journal of Agricultural and Biological Sciences, 6(3), 365-376. doi:10.3844/ajabssp.2011.365.376http://www.ti.com/lit/ds/symlink/cc1110f32.pdfhttp://www.comedia.com.hkOliver, J., & Perez Malumbres, M. (2008). On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements. IEEE Transactions on Circuits and Systems for Video Technology, 18(2), 237-248. doi:10.1109/tcsvt.2007.91396

In-line monitoring of chemical analysis processes using Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are very promising tools in the advanced automation of chemical-analysis processes. Basically, they are formed by many small devices - called sensor nodes or motes - that can obtain information from the surrounding area using appropriate transducers, and communicate it by suitable wireless-transmission systems. In this article, we study both the application of WSN technology to analytical chemistry and the new research fields for analytical chemistry opened up by the success of WSN applications. A basic "chemical-applied" description of WSNs is followed by the reasons for their implementation and their use in chemical-analysis processes, and comments on the most relevant contributions developed so far. Finally, this article also deals with future trends in this field. Key research challenges to be addressed to deliver remote, wireless, chemosensing systems include the development of low-cost, low-consumption sensors. (C) 2012 Elsevier Ltd. All rights reserved.Bonastre Pina, AM.; Capella Hernández, JV.; Ors Carot, R.; Peris Tortajada, M. (2012). In-line monitoring of chemical analysis processes using Wireless Sensor Networks. Trends in Analytical Chemistry. 34:111-125. doi:10.1016/j.trac.2011.11.009S1111253

An interference-tolerant nitrate smart sensor for Wireless Sensor Network applications

[EN] As a major contaminant in ground water, nitrate determination is a common practice in environmental analysis, especially the continuous and simultaneous monitoring of its concentration at many different points. For this task, sensor networks are a promising tool, although they require the use of sensors with special features, such as those of Ion Selective Electrodes (ISEs). Unfortunately, their measurements are – to a greater or lesser extent – affected by the presence of other coexisting (interfering) ions. A new methodology is then proposed in this work to deal with major interferences (chloride and bicarbonate in the case of nitrate determination), in such a way that the results obtained in the measurements of the content of NO3 − with a nitrate selective electrode can be considered as virtually error-free from these interferences. For this purpose, a new sensor node has been developed; it consists of three ISEs (NO3 −, Cl−, and HCO3 −) coupled to a low-consumption, low-cost microcontroller (a small chip containing all the computer components), which receives and processes all signals coming from the electrodes. This information is suitably treated, as described in detail in this paper, to provide an accurate estimation of the true value of NO3 − concentration. The application of this methodology results in an interference-tolerant nitrate smart sensor capable of being employed within a Wireless Sensor Network in the continuous monitoring of nitrate concentration in aquifers and rivers. © 2015 Elsevier B.V. All rights reserved.The authors gratefully acknowledge the financial support from the Valencian Regional Government under Research Project GV/2014/012, Polytechnic University of Valencia (Research Project UPV PAID-06-12) and Spanish Government (Research Projects CTM2011-29691-C02-01 and TIN2011-28435-C03-0).Capella Hernández, JV.; Bonastre Pina, AM.; Ors Carot, R.; Peris Tortajada, M. (2015). An interference-tolerant nitrate smart sensor for Wireless Sensor Network applications. Sensors and Actuators B: Chemical. 213:534-540. doi:10.1016/j.snb.2015.02.125S53454021

A step forward in the in-line river monitoring of nitrate by means of a wireless sensor network

This paper is based on our previous work consisting of the development and deployment of a wireless sensor network for the continuous in-line monitoring of the content of nitrates in a river in Eastern Spain. We present new contributions that significantly enhance its applicability, improve its features, and increase its reliability and useful life. For this purpose, an expert system has been developed in order to improve the features of the whole system operation in an intelligent, flexible, user friendly way. This expert system offers several policies to optimize the times at which measurements are to be carried out (and sent), sampling frequency being altered according to the system evolution, the user preferences and the application features. The implemented policies are as follows: (a) periodic transmission; (b) gradient transmission; (c) user request and (d) peer request. Additionally, in order to increase the reliability of the system, a triple modular redundant transducer in each sensor has been implemented, increasing dependability of the system with a very small affection of cost and consumption. Prior to the field trials, some laboratory experiments have been performed for parameter adjustment and checking purposes. As in the previous work, the proposed system has been deployed along a certain stretch of the river, its operation being studied and validated.Capella Hernández, JV.; Bonastre Pina, AM.; Ors Carot, R.; Peris Tortajada, M. (2014). A step forward in the in-line river monitoring of nitrate by means of a wireless sensor network. Sensors and Actuators B: Chemical. 195:396-403. doi:10.1016/j.snb.2014.01.039S39640319