an automatic aw som vhdl ip core generator

In this paper, the authors present a MATLAB IP generator for hardware accelerators of All-Winner Self-Organizing Maps (AW-SOM). AW-SOM is a modified version of Kohonen's Self Organizing Maps (SOM) algorithm, which is one of the most used Machine Learning algorithms for data clustering, and vector quantization. The architecture of the AW-SOM method is meant for hardware implementations, and its main feature is a processing speed almost independent to the number of neurons since each of them is processed in a parallel way; the parallelization can be easily exploited by hardware custom hardware designs. The IP generator is built-in MATLAB and provides the user with the possibility to design a custom and efficient hardware accelerator. Several settings can be set such as the number of features and the number of neurons. The target language is the VHSIC Hardware Description Language (VHDL). The generated IP cores can be used for the training of the model and a built-in function of the software can also check the clustering performances using its inference capabilities. The accelerators produced by the software have been also characterized in terms of max frequency, hardware resources, and power consumption. The authors performed the hardware implementations on a XILINX Virtex 7 xc7vx690t FPGA

A Feature Extractor IC for Acoustic Emission Non-destructive Testing

In this paper, we present the design and the implementation of a digital Application Specific Integrated Circuit (ASIC) for Acoustic Emission (AE) non-destructive testing. The AE non-destructive testing method is a diagnostic method used to detect faults in mechanically loaded structures and components. If a structure is subjected to mechanical load or stress, the presence of structural discontinuities releases energy in the form of acoustic emissions through the constituting material. The analysis of these acoustic emissions can be used to determine the presence of faults in several structures. The proposed circuit has been designed for IoT (Internet of Things) applications, and it can be used to simplify the existing procedures adopted for structural integrity verifications of pressurized metal tanks that, in some countries, they are based on periodic checks. The proposed ASIC is provided of Digital Signal Processing (DSP) capabilities for the extraction of the main four parameters used in the AE analysis that are the energy of the signal, the duration of the event, the number of the crossing of a certain threshold and finally the maximum value reached by the AE signal. The circuit is provided of an SPI interface capable of sending and receiving data to/from wireless transceivers to share information on the web. The DSP circuit has been coded in VHDL and synthesized in 90 nm technology using Synopsys. The circuit has been characterized in terms of area, speed, and power consumption. Experimental results show that the proposed circuit presents very low power consumption properties and low area requirements

comparison of low complexity algorithms for real time qrs detection using standard ecg database

Today, thanks to the development of advanced wearable devices, it is possible to track patient conditions outside hospital setting for several days. One of the most important bio-signals used for health analysis is the electrocardiographic (ECG) signal. It provides information about the heart rate, rhythm, and morphology of heart. Many algorithms are proposed over years for automated ECG analysis. Due to their computational complexity, not all these techniques can be implemented on wearable devices for real-time ECG detection. In this frame, a particular interest is toward the algorithms for automatic QRS detection. Different algorithms have been presented in the literature. Among all, more suitable class for the implementation on embedded systems is based on the use of signal derivatives and thresholds. These algorithms are composed by pre-processing stage, for the noise removal, and decision stage for the QRS detection. In literature, the different algorithms were discriminated only with respect to their pre-processing stages. Furthermore, not all algorithms were tested with standard database: this makes the results difficult to compare and evaluate. Moreover, the algorithms performance in case of pathological behaviours was not compared. This paper is motivated by the need to perform a comparison of the whole algorithms, both pre-processing and decision stages, under a standard database (MIT-BIH ECG database of Physionet), either for non-pathological and pathological signals. The results confirm that the Pan & Tompkins algorithm has the best performance in terms of QRS complex detection. However, in some cases, its performance is comparable with the other algorithms ones. For this reason, in the applications in which the reduced of computational complexity is an important constraint, it is possible to implemented algorithms with comparable performance but with lesser complexity with respect to P&T algorithm

E-health-IoT Universe: A Review

The Internet of Things (IoT) devices are able to collect and share data directly with other devices through the cloud environment, providing a huge amount of information to be gathered, stored and analyzed for data-analytics processes. The scenarios in which the IoT devices may be useful are amazing varying, from automotive, to industrial automation or remote monitoring of domestic environment. Furthermore, has been proved that healthcare applications represent an important field of interest for IoT devices, due to the capability of improving the access to care, reducing the cost of healthcare and most importantly increasing the quality of life of the patients. In this paper, we analyze the state-of-art of IoT in medical environment, illustrating an extended range of IoT-driven healthcare applications that, however, still need innovative and high technology-based solutions to be considered ready to market. In particular, problems regarding characteristics of response-time and precision will be examined.  Furthermore, wearable and energy saving properties will be investigated in this paper and also the IT architectures able to ensure security and privacy during the all data-transmission process. Finally, considerations about data mining applications, such as risks prediction, classification and clustering will be provided, that are considered fundamental issues to ensure the accuracy of the care processes

Smarter City: Smart Energy Grid based on Blockchain Technology

The improvement of the Quality of Life (QoL) and the enhancement of the Quality of Services (QoS) represent the main goal of every city evolutionary process. It is possible making cities smarter promoting innovative solutions by use of Information and Communication Technology (ICT) for collecting and analysing large amounts of data generated by several sources, such as sensor networks, wearable devices, and IoT devices spread among the city. The integration of different technologies and different IT systems, needed to build smart city applications and services, remains the most challenge to overcome. In the Smart City context, this paper intends to investigate the Smart Environment pillar, and in particular the aspect related to the implementation of Smart Energy Grid for citizens in the urban context. The innovative characteristic of the proposed solution consists of using the Blockchain technology to join the Grid, exchanging information, and buy/sell energy between the involved nodes (energy providers and private citizens), using the Blockchain granting ledger

e health iot universe a review

The Internet of Things (IoT) devices are able to collect and share data directly with other devices through the cloud environment, providing a huge amount of information to be gathered, stored and analyzed for data-analytics processes. The scenarios in which the IoT devices may be useful are amazing varying, from automotive, to industrial automation or remote monitoring of domestic environment. Furthermore, has been proved that healthcare applications represent an important field of interest for IoT devices, due to the capability of improving the access to care, reducing the cost of healthcare and most importantly increasing the quality of life of the patients. In this paper, we analyze the state-of-art of IoT in medical environment, illustrating an extended range of IoT-driven healthcare applications that, however, still need innovative and high technology-based solutions to be considered ready to market. In particular, problems regarding characteristics of response-time and precision will be examined. Furthermore, wearable and energy saving properties will be investigated in this paper and also the IT architectures able to ensure security and privacy during the all data-transmission process. Finally, considerations about data mining applications, such as risks prediction, classification and clustering will be provided, that are considered fundamental issues to ensure the accuracy of the care processes