In cyber-physical systems, such as modern industrial plants, complex software is an essential part that enables cost-effective and flexible operation. However, this complexity increases the probability of problems that only reveal themselves after the deployment. This is even more important if security aspects are involved. Therefore, providing the possibility for software updates is an important building block in the design of industrial plants. This paper presents a holistic concept for software updates in an industrial plant with thousands of wirelessly connected embedded devices. Using wireless technology imposes additional difficulties in terms of data rate, packet size and reliability that have to be addressed in particular. The contribution also includes an analytical model to estimate the time until a new firmware is distributed. Evaluations carried out on hardware as well as in the OMNeT++ simulator demonstrate the applicability and scalability of the proposed approach.
Rising crude oil prices and worldwide awareness of environmental issues have resulted in increased research and development of energy storage systems. Batteries are one of the most attractive energy storage systems because of their high efficiency and low pollution. Because of their high-energy densities and long lifetimes, lithium-ion batteries are increasingly used not only in electrical vehicles, but also in other applications. A key point in the management of lithium-ion batteries is expanding their energy storage capability and lifetimes. To achieve this, a fundamental embedded system is the battery management system (BMS) needed to ensure optimal, reliable and safe operation of the battery. Modelling and characterization of the single cells and an efficient simulation environment is fundamental for the development of an efficient BMS. This work presents a study of the statistical variations of the characteristic parameters of the single cells on the performances of a battery pack. The Montecarlo method on the SystemC-WMS simulations has been used.
This paper presents a design for a low-cost research robot based on the small size of the Hexbug Spider toy1. Our basic modification replaces the robot head with a 3D-printed adapter, consisting of two parts to provide space for sensors, a larger battery, and a printed circuit board (PCB) with Arduino microcontroller, Wi-Fi module, and motor controller. We address the assembling process of such a robot and the programming using Arduino studio. The presented prototype costs less than 70 Euro, and is suitable for swarm robotic experiments and educational purposes.
The growing market of electronic appliances is nowadays introducing a new kind of problem: the disposal management of a great quantity of broken or simply outdated electric and electronic devices. Sometimes the equipment contain dangerous or precious materials, that must be handled carefully. Furthermore, several good and valuable components on broken equipment could be reused. In this work, we present a Web based system conceived and designed to maintain all those information that can improve the end-of-life management of an electronic appliance. The cloud database can be easily accessed using the RFId technology, allowing the traceability of the equipment and the single components in the manufacturing, use, reuse and end-of-life phases.
Network firewall rules are usually written by administrators or automated intrusion detection systems and often contain inconsistencies. Therefore, it is fundamental to ensure that only an absolutely correct configuration is active. In this paper, we design an open source conflict resolution framework (C application and Linux firewall kernel module on top of netfilter) that can be used as a constant independent system auditor, automatically detecting and resolving conflicts in firewall rules. Preliminary analysis from our implementation on ARM-based embedded systems examines efficiency and scalability of our framework.
Detailed memory access traces are extremely helpful for system partitioning and optimization in the context of hardware/software codesign, especially in early design stages. The prevalent technique for the generation of such traces is interpretive instruction set simulation which, however, depends on detailed modeling and further results in poor performance. With compiled simulation techniques, performance can be improved, but accurate memory access traces come at the expense of higheffort, complex, and inflexible toolchains. In order to overcome these bottlenecks, we present a hybrid profiling method that combines benefits from both worlds for a flexible workflow at minimum modeling effort. Experimental results confirm our method the same accuracy as interpretive simulation while being 50.3 times faster on average. Even compared to compiled simulation-based profiling, we achieve a mean speedup of 1.8 at 11.9% higher accuracy.
To analyse user behaviour and energy consumption data in contemporary and future households, we need to monitor electrical appliance features as well as ambient appliance features. For this purpose, a distributed measurement system is required, which measures the entire power consumption of the household, the power consumption of selected household appliances, and the effect of these appliances on their environment. In this paper we present a distributed measurement system that records and monitors electrical household appliances. Our low-cost measurement system integrates the YaY smart meter, a set of smart plugs, and several networked ambient sensors. In conjunction with energy advisor tools the presented measurement system provides an efficient low-cost alternative to commercial energy monitoring systems by surpassing them with machine learning techniques, appliance identification methods, and applications based on load disaggregation.
A huge upheaval emerges from the transition to autonomous vehicles in the domain of road vehicles, ongoing with a change in the vehicle architecture. Many sensors and Electronic Control Units are added to the current vehicle architecture and further safety requirements like reliability become even more necessary. In this paper we present a potential evolution of the Electrical/Electronic-Architecture, including a Zone Architecture, to enable future functionality. We reveal the impact on the communication network concerning these architectures and present a potential communication technology to facilitate such architectures.
Electrocardiography is a simple clinically useful non-invasive technique to evaluate the activity of the heart. The heart rate is very variable parameter and sometimes reaches very high values. In these cases, the frequency band of the electrocardiographic (ECG) signal overlaps the band of the surface electromyographic (sEMG) signal, which it represents an interfering signal. The aim of the present study is to show how the Segmented Beat Modulation Method (SBMM) can be used to clean the ECG signal from muscular noise. To this aim, a real ECG signal (characterized by a fast heart rate and corrupted by muscular noise) was acquired from a violinist while he was playing. Results indicate that the ECG and the sEMG signal can be separated without losing morphological features and spectral components of both signals. Thus SBMM is a promising tool for cleaning the ECG signal from muscular noise.
This paper presents a technique to extend the transmission range over a single RS-485 cable, without requiring installation of expensive and cumbersome RS-485 repeaters, to virtually unlimited distances, while simultaneously improving transmission speeds between closer nodes. This was accomplished by leveraging the routing capabilities embedded into each node that implements the recently released and extremely lightweight ToLHnet protocol. With it, each network node can act as a sort of “smart repeater” only when there is need to, optimizing the overall network throughput. The key ideas underlying the routing strategies are here described, together with details of a prototype node and experimental results demonstrating transmission at distances well above the traditional limit.
An Arduino board, equipped with a Controller Area Network interface and Bluetooth Low Energy has been programmed to read the information provided by the Battery Management System of an electric vehicle. The information are available to the user through a smartphone app.
The assessment of the fetal well-being is accomplished with the monitoring of fetal cardiac activity. In presence of risk labor, direct fetal electrocardiography (fECG) can be obtained by positioning an electrode on the fetal scalp. However, its invasiveness and application limited to labor have led to the introduction of the indirect (noninvasive) fECG, obtained by applying the electrodes on the maternal abdomen. The abdominal recordings are corrupted by the maternal ECG (mECG) that often covers the fECG (the signal of interest). To extract the fECG, the mECG has to be estimated and then subtracted from the abdominal recording. To this aim, template-based techniques are often applied. However, such techniques are typically not able to reproduce physiological heart rate (HR) and morphological variability. To overcome this limit, an innovative template-based filtering technique termed the Segmented-Beat Modulation Method (SBMM) has recently been proposed. To evaluate its ability to extract the fECG, SBMM is applied here to an abdominal recording. Direct fECG was simultaneously recorded for comparison. Each RR interval of the direct fECG was correlated with the corresponding RR interval of the indirect fECG, and a statistically significant strong correlation (ρ=0.86, P<;10-26) was found. Thus, the SBMM proved to be a potentially useful tool to provide a reliable fECG signal (extracted from an abdominal recording) that can be used for monitoring the fetus health conditions.
In this paper an embedded system for accurate control of torque, speed and position of DC motors which actuate the joints of a robotic leg is presented. The proposed embedded system is not based on dedicated and expensive motor controllers but on a general pourpose embedded board equipped with a 32bit microcontroller. For each motor the embedded system can selectively operate in three different control modes: torque, speed and position, to control concurrently at least three DC motors with different control tasks. Each motor is simply equipped with a rotary encoder and a low-cost current sensor which provide measurements of velocity and current as feedback signals. The experimental results show that the embedded controller is able to regulate the motor variables as expected by simulation results. Although the embedded controller was designed for the proposed robotic application, it is applicable to other systems where the concurrent control of several DC-motors is required.
The rearing of bees is a quite difficult job since it requires experience and time. Beekeepers are used to take care of their bee colonies observing them and learning to interpret their behavior. Despite the rearing of bees represents one of the most antique human habits, nowadays bees risk the extinction principally because of the increasing pollution levels related to human activity. It is important to increase our knowledge about bees in order to develop new practices intended to improve their protection. These practices could include new technologies, in order to increase profitability of beekeepers and economical interest related to bee rearing, but also innovative rearing techniques, genetic selections, environmental politics and so on. Moreover bees, since they are very sensitive to pollution, are considered environmental indicators, and the research on bees could give important information about the conditions of soil, air and water. In this paper we propose a real hardware and software solution for apply the internet-of-things concept to bees in order to help beekeepers to improve their business and collect data for research purposes.
One of the major problems with electric vehicles is the battery. The battery must be adequately monitored in order to optimize its performances and to maximize its life, to know when it's time to recharge it, or when the charging has been completed, or it's time to buy a new one. The battery's monitoring is the goal of the battery management system (BMS), which must be carefully designed. Moreover, the BMS must report its data to the outer world, and this means that it cannot work alone. If we want to use some kind of simulation to help the design of an effective BMS, we need a simulation model that can be easily attached to other hardware simulation models, such as CAN bus' or Bluetooth models. In this work we present and validate a BMS SystemC simulation model. Both the design and the validation of this BMS are carried on using real-world scenarios and data.
The widespread use of electronic equipments such as smartphones, tablets and digital cameras is largely contributing to the relentless progress of memories devices based on nonvolatile flash technology. Volatile memories, typically based on DRAM technology, are characterized by higher cost and performance when compared to non-volatile memories; in the design of an electronic device it is important to balance the utilization of these two storage solutions to meet different needs in terms of processing speed and long-term data retention. This paper reports the development of the system-level model of a controller capable of optimizing the use of NAND type flash memories, for the storage and the playback of audio samples in real-time music applications; the aim is the reduction of the quantity of system SDRAM memory thus lowering the cost of the final product, while still providing the user with the most high-fidelity sound experience.
Due to its relative simplicity, the JPEG compression algorithm requires less hardware or software resources with respect to new compression algorithms, for example the JPEG2000 and the JPEG XR. This makes it suitable for low-power applications. Moreover, features embedded in the JPEG2000 and the JPEG XR, such as the scalability of the image stream, can be added to the main JPEG core, making an encoder useful for example in a video surveillance wireless network. Nevertheless, actual JPEG dedicated hardware realizations do not implement many features of the compression standard. In this work, we developed several JPEG encoder architectures with full real-time reconfigurability and support for the restart intervals and, for a simple scalability mechanism, the scan scheme. These features make the architectures suitable for the use in low-bandwidth, low-power wireless networks. The JPEG encoder architectures have been developed starting from a SystemC model and then implemented in a FPGA.
The current automotive IC sector counts hundreds of different systems, standard products or ASICs, for the inductive load drivers application. Many of them, such injector drivers, DC/brushless motor drivers, solenoid drivers, are designed to work in a specific operating mode, with fixed architecture and parameters. Since the need of different applications increases, a flexible approach to the design is mandatory. The state of the art offers only software-oriented systems to overcome these problems, which require embedded MCU. In this paper, an alternative system design for inductive load driver is proposed. It is based on an optimized and flexible architecture. With this flexible approach, it is possible to implement most of the topology scheme with regulation feedback and a programmable solution for shaping the current waveform into the loads.
This paper presents a design for a low-cost research robot based on the chassis of a Hexbug Spider, a remote controlled toy robot. Our modification replaces the robot head with a 3d printed adapter part which provides space for sensors, a larger battery, and a microcontroller board. In a second part of the paper we address the manufacturing process of such a robot. The presented robot costs far less than 100 Euro and is suitable for swarm robotic experiments. The hexapod locomotion makes the robot attractive for applications where a two wheel differential drive cannot be used. Our modification is published as open hardware and open source to allow further customizations.
The ability to estimate the distance covered and the orientation of a person, regardless from where he or she is located, is an important aspect in various research areas and in particular in Pedestrian Navigation Systems (PNS) for emergency responders. In this paper we present a PNS based on a wearable wireless device attached to the instep of the pedestrian. The implemented real time algorithm, is able to identify pedestrian's strides, estimating theirs length and direction by using information provided from an embedded Inertial Measurement Unit (IMU). The proposed device is also equipped with MicroSD slot and Bluetooth module for data storage and for sending information in real time. The proposed system has been tested through an objective experimental method in which ten volunteers were walking along three different tracks, five times each, keeping the IMU attached to the instep. In the first trial subjects walked along a straight path that is 90m long, in the second they walked twice along a rectangular path with long side equal to 15m and short side equal to 7.5m and in the last they walked 400m along a standard athletics track. For each test we computed absolute and average error. The results show that the average error is 3.52% for the straight track, 1.09% for the rectangular track and 3.71% for the elliptic track.
