Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Low-cost modular devices for on-road vehicle detection and characterisation

[EN] Detecting and characterising vehicles is one of the purposes of embedded systems used in intelligent environments. An analysis of a vehicle¿s characteristics can reveal inappropriate or dangerous behaviour. This detection makes it possible to sanction or notify emergency services to take early and practical actions. Vehicle detection and characterisation systems employ complex sensors such as video cameras, especially in urban environments. These sensors provide high precision and performance, although the price and computational requirements are proportional to their accuracy. These sensors offer high accuracy, but the price and computational requirements are directly proportional to their performance. This article introduces a system based on modular devices that is economical and has a low computational cost. These devices use ultrasonic sensors to detect the speed and length of vehicles. The measurement accuracy is improved through the collaboration of the device modules. The experiments were performed using multiple modules oriented to different angles. This module is coupled with another specifically designed to detect distance using previous modules¿ speed and length data. The collaboration between different modules reduces the speed relative error ranges from 1 to 5%, depending on the angle configuration used in the modules.This work was by the Spanish Science and Innovation Ministry: CICYT project PRESECREL: "Models and platforms for predictable, secure and reliable industrial information technology systems" PID2021-124502OB-C41. Funding for open access charge: CRUE-Universitat Politecnica de Valencia.Poza-Lujan, J.; Uribe-Chavert, P.; Posadas-Yagüe, J. (2023). Low-cost modular devices for on-road vehicle detection and characterisation. Design Automation for Embedded Systems. 27(1-2):85-102. https://doi.org/10.1007/s10617-023-09270-y85102271-2Broy M, Cengarle MV, Geisberger E (2012) Cyber-physical systems: imminent challenges. In: Monterey workshop, pp 1–28. SpringerWolf W (2009) Cyber-physical systems. IEEE Ann Hist Comput 42(03):88–89Serpanos D (2018) The cyber-physical systems revolution. Computer 51(3):70–73Hichri Y, Dahi S, Fathallah H (2021) Candidate architectures for emerging IOV: a survey and comparative study. Des Autom Embed Syst 25(4):237–263Canas V, Garcia A, de Las-Morenas J, Blanco J (2019) Modular and reconfigurable platform as new philosophy for the development of updatable vehicular electronics. Rev Iberoam de Automática e Inform Industr 16(2):200–211Asselin-Miller N, Biedka M, Gibson G, Kirsch F, Hill N, White B, Uddin K (2016) Study on the deployment of c-its in Europe: final report. Rep for DG MOVE MOVE/C 3:2014–794Corli A, Malaguti L (2021) Wave fronts in traffic flows and crowds dynamics. In: Cicognani M, Del Santo D, Parmeggiani A, Reissig M (eds) Anomalies in partial differential equations. Springer, Cham, pp 167–189Maity S, Bhattacharyya A, Singh PK, Kumar M, Sarkar R (2022) Last decade in vehicle detection and classification: a comprehensive survey. Arch Comput Methods Eng 28:1–38Sun Z, Bebis G, Miller R (2004) On-road vehicle detection using optical sensors: a review. In: Proceedings. The 7th International IEEE Conference on Intelligent Transportation Systems (IEEE Cat. No. 04TH8749), pp 585–590. IEEELi W, Li H, Wu Q, Chen X, Ngan KN (2019) Simultaneously detecting and counting dense vehicles from drone images. IEEE Trans Industr Electron 66(12):9651–9662Messoussi O, Magalhães FGd, Lamarre F, Perreault F, Sogoba I, Bilodeau G-A, Nicolescu G (2021) Vehicle detection and tracking from surveillance cameras in Urban scenes. In: International symposium on visual computing, pp 191–202. SpringerLozano Dominguez JM, Mateo Sanguino TJ (2019) Review on v2x, i2x, and p2x communications and their applications: a comprehensive analysis over time. Sensors 19(12):2756Qian X, Hao L (2020) Performance analysis of cooperative sensing over time-correlated Rayleigh channels in vehicular environments. Electronics 9(6):1004Hidalgo C, Marcano M, Fernandez G, Perez J (2020) Cooperative maneuvers applied to automated vehicles in real and virtual environments. Rev Iberoam de Autom e Inform industr 17(1):56–65Scaglia G, Serrano ME, Albertos Pérez P (2020) Control de trayectorias basado en álgebra lineal. Rev Iberoam de Autom e Inform industr 17(4):344–353Chen Z, Wu C, Huang Z, Lyu N, Hu Z, Zhong M, Cheng Y, Ran B (2017) Dangerous driving behavior detection using video-extracted vehicle trajectory histograms. J Intell Transport Syst 21(5):409–421Celik T, Kusetogullari H (2009) Solar-powered automated road surveillance system for speed violation detection. IEEE Trans Industr Electron 57(9):3216–3227de Oliveira M, Teixeira R, Sousa R, Tavares Gonçalves EJ, et al (2021) An agent-based simulation to explore communication in a system to control urban traffic with smart traffic lightsAdarsh S, Kaleemuddin SM, Bose D, Ramachandran K (2016) Performance comparison of infrared and ultrasonic sensors for obstacles of different materials in vehicle/robot navigation applications. IOP Conf Ser Mater Sci Eng 149:012141Appiah O, Quayson E, Opoku E (2020) Ultrasonic sensor based traffic information acquisition system; a cheaper alternative for its application in developing countries. Sci Afr 9:00487Matsuo T, Kaneko Y, Matano, M (1999) Introduction of intelligent vehicle detection sensors. In: Proceedings 199 IEEE/IEEJ/JSAI international conference on intelligent transportation systems (Cat. No. 99TH8383), pp 709–713. IEEEJo Y, Choi J, Jung I (2014) Traffic information acquisition system with ultrasonic sensors in wireless sensor networks. Int J Distrib Sens Netw 10(5):961073Li SE, Li G, Yu J, Liu C, Cheng B, Wang J, Li K (2018) Kalman filter-based tracking of moving objects using linear ultrasonic sensor array for road vehicles. Mech Syst Signal Process 98:173–189Jeon S, Kwon E, Jung I (2014) Traffic measurement on multiple drive lanes with wireless ultrasonic sensors. Sensors 14(12):22891–22906Stiawan R, Kusumadjati A, Aminah NS, Djamal M, Viridi S (2019) An ultrasonic sensor system for vehicle detection application. J Phys Conf Ser 1204:012017Marwedel P (2021) Embedded system design: embedded systems foundations of cyber-physical systems, and the internet of things. Springer, New YorkSwanson DC (2011) Signal Processing for intelligent sensor systems with MATLAB. CRC Press, Boca RatonBae I, Ji U (2019) Outlier detection and smoothing process for water level data measured by ultrasonic sensor in stream flows. Water 11(5):951Zhao H, Wang Z (2011) Motion measurement using inertial sensors, ultrasonic sensors, and magnetometers with extended Kalman filter for data fusion. IEEE Sens J 12(5):943–953Ting J-A, Theodorou E, Schaal S (2007) Learning an outlier-robust Kalman filter. Eur Conf Mach Learn 25:748–756Johnson NL (1961) A simple theoretical approach to cumulative sum control charts. J Am Stat Assoc 56(296):835–840Pierre R.Bertrand, Hadouni D (2015) Change point detection by filtered derivative with p-value : choice of the extra-parameters. Working paper or preprint. https://hal.science/hal-01240885Găşpăresc G, Gontean A (2014) Performance evaluation of ultrasonic sensors accuracy in distance measurement. In: 2014 11th International symposium on electronics and telecommunications (ISETC), pp 1–4. IEEETsitsiklis JN (1988) Decentralized detection by a large number of sensors. Math Control Signals Syst 1(2):167–182Koldobsky A (1998) Second derivative test for intersection bodies. Adv Math 136(1):15–25Lee M, Newman RE, Latchman HA, Katar S, Yonge L (2003) Homeplug 1.0 powerline communication lans-protocol description and performance results. Int J Commun Syst 16(5):447–473Poza-Lujan JL, Uribe-Chavert P, Sáenz-Peñafiel J-J, Posadas-Yagüe J-L (2021) Distributing and processing data from the edge. a case study with ultrasound sensor modules. Int Symp Distrib Comput Artif Intell 95:190–199Marko D, Hrubỳ D (2020) Distance measuring in vineyard row using ultrasonic and optical sensors. In: Proceeding of 22 Nd international conference of Young scientists. Praha: Česká Zemědělská univerzita, pp 194–204Semiconductors P (2000) The i2c-bus specification. Philips Semicond 9397(750):00954Huh J-H, Seo K (2017) An indoor location-based control system using Bluetooth beacons for IoT systems. Sensors 17(12):2917Gandhi MM, Solanki DS, Daptardar RS, Baloorkar NS (2020) Smart control of traffic light using artificial intelligence. In:2020 5th IEEE international conference on recent advances and innovations in engineering (ICRAIE), pp 1–6. IEEEUribe Chavert P, Gandhi MM (2022) Vehicle speed and length detector with ultrasound sensor and different angles. https://doi.org/10.5281/zenodo.7215268.‘github.com/puch18ou/

Design Criteria to Architect Continuous Experimentation for Self-Driving Vehicles

The software powering today's vehicles surpasses mechatronics as the dominating engineering challenge due to its fast evolving and innovative nature. In addition, the software and system architecture for upcoming vehicles with automated driving functionality is already processing ~750MB/s - corresponding to over 180 simultaneous 4K-video streams from popular video-on-demand services. Hence, self-driving cars will run so much software to resemble "small data centers on wheels" rather than just transportation vehicles. Continuous Integration, Deployment, and Experimentation have been successfully adopted for software-only products as enabling methodology for feedback-based software development. For example, a popular search engine conducts ~250 experiments each day to improve the software based on its users' behavior. This work investigates design criteria for the software architecture and the corresponding software development and deployment process for complex cyber-physical systems, with the goal of enabling Continuous Experimentation as a way to achieve continuous software evolution. Our research involved reviewing related literature on the topic to extract relevant design requirements. The study is concluded by describing the software development and deployment process and software architecture adopted by our self-driving vehicle laboratory, both based on the extracted criteria.Comment: Copyright 2017 IEEE. Paper submitted and accepted at the 2017 IEEE International Conference on Software Architecture. 8 pages, 2 figures. Published in IEEE Xplore Digital Library, URL: http://ieeexplore.ieee.org/abstract/document/7930218

Deep Drone Racing: From Simulation to Reality with Domain Randomization

Dynamically changing environments, unreliable state estimation, and operation under severe resource constraints are fundamental challenges that limit the deployment of small autonomous drones. We address these challenges in the context of autonomous, vision-based drone racing in dynamic environments. A racing drone must traverse a track with possibly moving gates at high speed. We enable this functionality by combining the performance of a state-of-the-art planning and control system with the perceptual awareness of a convolutional neural network (CNN). The resulting modular system is both platform- and domain-independent: it is trained in simulation and deployed on a physical quadrotor without any fine-tuning. The abundance of simulated data, generated via domain randomization, makes our system robust to changes of illumination and gate appearance. To the best of our knowledge, our approach is the first to demonstrate zero-shot sim-to-real transfer on the task of agile drone flight. We extensively test the precision and robustness of our system, both in simulation and on a physical platform, and show significant improvements over the state of the art.Comment: Accepted as a Regular Paper to the IEEE Transactions on Robotics Journal. arXiv admin note: substantial text overlap with arXiv:1806.0854

A digest of the main insights and achievements of the project IM-CLeVeR - Intrinsically Motivated Cumulative Learning Versatile Robots

This document is directed to illustrate the main achievements and insights gained by the IM-CLeVeR project. These achievements suggest new hypothesis of research on intrinsic motivations and autonomous cumulative open-ended learning both for running new neuroscience and psychology experiments and for building future autonomously developing robots. IM-CLeVeR is a project funded by the European Commission under the 7th Framework Programme (FP7/2007-2013), \u27\u27Challenge 2 - Cognitive Systems, Interaction, Robotics\u27\u27, grant agreement No. ICTIP-231722

Final report key contents: main results accomplished by the EU-Funded project IM-CLeVeR - Intrinsically Motivated Cumulative Learning Versatile Robots

This document has the goal of presenting the main scientific and technological achievements of the project IM-CLeVeR. The document is organised as follows: 1. Project executive summary: a brief overview of the project vision, objectives and keywords. 2. Beneficiaries of the project and contacts: list of Teams (partners) of the project, Team Leaders and contacts. 3. Project context and objectives: the vision of the project and its overall objectives 4. Overview of work performed and main results achieved: a one page overview of the main results of the project 5. Overview of main results per partner: a bullet-point list of main results per partners 6. Main achievements in detail, per partner: a throughout explanation of the main results per partner (but including collaboration work), with also reference to the main publications supporting them

Futures of Fixing : Exploring the life of product users in circular economy repair society scenarios

A Circular Economy (CE) constitutes one pathway towards realising sustainable productionand consumption. Here, the repair of broken products (compared to replacement) consti-tutes an important strategy to keep products in the economy for longer, thereby reducingwaste, as well as the need to extract resources and emit pollution in the manufacture of areplacement product. In today’s world, repair does not necessarily constitute the naturalresponse to product breakage. However, increasing legislative efforts and grassroots move-ments are attempting to change that and make repair accessible, affordable and culturallyacceptable. The question is what such a society – where repair is normalised – would be like

A cognitive robotic ecology approach to self-configuring and evolving AAL systems

Robotic ecologies are systems made out of several robotic devices, including mobile robots, wireless sensors and effectors embedded in everyday environments, where they cooperate to achieve complex tasks. This paper demonstrates how endowing robotic ecologies with information processing algorithms such as perception, learning, planning, and novelty detection can make these systems able to deliver modular, flexible, manageable and dependable Ambient Assisted Living (AAL) solutions. Specifically, we show how the integrated and self-organising cognitive solutions implemented within the EU project RUBICON (Robotic UBIquitous Cognitive Network) can reduce the need of costly pre-programming and maintenance of robotic ecologies. We illustrate how these solutions can be harnessed to (i) deliver a range of assistive services by coordinating the sensing & acting capabilities of heterogeneous devices, (ii) adapt and tune the overall behaviour of the ecology to the preferences and behaviour of its inhabitants, and also (iii) deal with novel events, due to the occurrence of new user's activities and changing user's habits

Connected dependability cage approach for safe automated driving

Automated driving systems can be helpful in a wide range of societal challenges, e.g., mobility-on-demand and transportation logistics for last-mile delivery, by aiding the vehicle driver or taking over the responsibility for the dynamic driving task partially or completely. Ensuring the safety of automated driving systems is no trivial task, even more so for those systems of SAE Level 3 or above. To achieve this, mechanisms are needed that can continuously monitor the system’s operating conditions, also denoted as the system’s operational design domain. This paper presents a safety concept for automated driving systems which uses a combination of onboard runtime monitoring via connected dependability cage and off-board runtime monitoring via a remote command control center, to continuously monitor the system’s ODD. On one side, the connected dependability cage fulfills a double functionality: (1) to monitor continuously the operational design domain of the automated driving system, and (2) to transfer the responsibility in a smooth and safe manner between the automated driving system and the off-board remote safety driver, who is present in the remote command control center. On the other side, the remote command control center enables the remote safety driver the monitoring and takeover of the vehicle’s control. We evaluate our safety concept for automated driving systems in a lab environment and on a test field track and report on results and lessons learned