Low-power grating detection system chip for high-speed low-cost length and angle precision measurement

Pedestrian detection is one of the key problems in the emerging self-driving car industry. In addition, the Histogram of Gradients (HOG) algorithm proved to provide good accuracy for pedestrian detection. Many research works focused on accelerating HOG algorithm on FPGA (Field-Programmable Gate Array) due to its low-power and high-throughput characteristics. In this paper, we present an energy-efficient HOG-based implementation for pedestrian detection system on a low-cost FPGA system-on-chip platform. The hardware accelerator implements the HOG computation and the Support Vector Machine classifier, the rest of the algorithm is mapped to software in the embedded processor. The hardware runs at 50 Mhz (lower frequency than previous works), thus achieving the best pixels processed per clock and the lower power design.

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Integration of highly anisotropic multiferroic BaTiO3–Fe nanocomposite thin films on Si towards device applications

Nanoscale Advances ◽

10.1039/d0na00405g ◽

2020 ◽

Vol 2 (9) ◽

pp. 4172-4178

Author(s):

Matias Kalaswad ◽

Bruce Zhang ◽

Xuejing Wang ◽

Han Wang ◽

Xingyao Gao ◽

...

Keyword(s):

Thin Films ◽

Power Consumption ◽

Low Power ◽

High Speed ◽

Low Cost ◽

Low Power Consumption ◽

Silicon Substrates ◽

Critical Step ◽

Nanocomposite Thin Films ◽

Device Applications

Integration of highly anisotropic multiferroic thin films on silicon substrates is a critical step towards low-cost devices, especially high-speed and low-power consumption memories.

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Performance Analysis of Mail Clients on Low Cost Computer With ELGamal and RSA Using SNORT

Advances in Systems Analysis, Software Engineering, and High Performance Computing - Handbook of Research on Pattern Engineering System Development for Big Data Analytics ◽

10.4018/978-1-5225-3870-7.ch020 ◽

2018 ◽

pp. 332-353

Author(s):

Sreerama Murthy Kattamuri ◽

Vijayalakshmi Kakulapati ◽

Pallam Setty S.

Keyword(s):

Intrusion Detection ◽

Low Power ◽

Intrusion Detection System ◽

Detection System ◽

Low Cost ◽

Raspberry Pi ◽

Ip Address ◽

Intrusion Prevention ◽

Plain Text ◽

Intrusion Prevention System

An intrusion detection system (IDS) focuses on determining malicious tasks by verifying network traffic and informing the network administrator for restricting the user or source or source IP address from accessing the network. SNORT is an open source intrusion detection system (IDS) and SNORT also acts as an intrusion prevention system (IPS) for monitoring and prevention of security attacks on networks. The authors applied encryption for text files by using cryptographic algorithms like Elgamal and RSA. This chapter tested the performance of mail clients in low cost, low power computer Raspberry Pi, and verified that SNORT is efficient for both algorithms. Within low cost, low power computer, they observed that as the size of the file increases, the run time is constant for compressed data; whereas in plain text, it changed significantly.

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The Design and Application of Multiplex Ground Temperature Detection System of Low Power Consumption Based on CAN Bus

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.568-570.497 ◽

2014 ◽

Vol 568-570 ◽

pp. 497-500

Author(s):

Jin Mei Liu ◽

Xiao Qiong Yao ◽

Pei Pei Liu

Keyword(s):

Power Consumption ◽

Low Power ◽

Can Bus ◽

Detection System ◽

Low Cost ◽

Temperature Data ◽

Ground Temperature ◽

Low Power Consumption ◽

Temperature Detection ◽

Channel Temperature

This paper introduces a kind of low power ground temperature monitoring system based on CAN bus, the detection system adopts DS18B20 temperature sensor as the detecting element, under a machine with low power consumption of processor MSP430 MCU multi-channel temperature data collection, PC processors SMT32 is adopted to improve the data receiving and analysis. The ground temperature detection system has realized the low power consumption, strong anti-interference ability, low cost, has wide use value.

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Application Research on Precision Detection of Small Gear with Composite Edge Detection Method

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.333-335.1123 ◽

2013 ◽

Vol 333-335 ◽

pp. 1123-1128

Author(s):

Xin Luo ◽

Li Ming Wu ◽

De Zhi Zeng

Keyword(s):

Edge Detection ◽

Real Time ◽

High Speed ◽

Dynamic Range ◽

Detection Method ◽

Detection System ◽

Structural Characteristics ◽

Low Cost ◽

Edge Image ◽

Edge Detection Method

Vision-based measurement method can be widely used for a variety of real-time and online precision measurements, and particularly well suited for dynamic real-time precision measurement of geometry parameters of the part, which has advantages of non-contact, high-speed, big dynamic range, rich amount of information, and relatively low cost. After the study of vision-based online detection system of small gear, we propose a composite subpixel edge detection method, which combines the four-way weighted differential algorithm based on the classic Sobel operator and OFMM (Orthogonal Fourier-Mellin Moment), aiming at achieving the precision location of the subpixel edge firstly. And then detect tooth profile defects rapidly through scanning circularly the edge image, according to the structural characteristics of gears. The theoretical analysis and experimental results show that the detection method has so high accuracy and speed that it can meet the industrial online tests requirements.

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High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection

Sensors ◽

10.3390/s22020474 ◽

2022 ◽

Vol 22 (2) ◽

pp. 474

Author(s):

Elio Hajj Assaf ◽

Cornelius von von Einem ◽

Cesar Cadena ◽

Roland Siegwart ◽

Florian Tschopp

Keyword(s):

Long Range ◽

High Precision ◽

High Speed ◽

Detection System ◽

Low Cost ◽

Obstacle Detection ◽

Numerical Control ◽

Railway Network ◽

Lever System ◽

Novel Approach

Increasing demand for rail transportation results transportation by rail, resulting in denser and more high-speed usage of the existing railway network, making makes new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the greatlarge weights of trains lead to long braking distances—all of which necessitates Long braking distances, due to high travelling speeds and the massive weight of trains, necessitate a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate enoughdata to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use ahigh-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a novel approach to detecting railway obstacles by developinga high-precision pointing mechanism, for the use in a future novel railway obstacle detection system In this work such a high-precision pointing mechanism is developed, capable of targeting aiming a 1D-LiDAR at humans or objects at the required distance. This approach addresses To address the challenges of a low target pricelimited budget, restricted access to high-precision machinery and equipment as well as unique requirements of our target application., a novel pointing mechanism has been designed and developed. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and cheaplow-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.

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High Speed Network Intrusion Detection System (NIDS) using Low Power Precomputation Based Content Addressable Memory

Computers Materials & Continua ◽

10.32604/cmc.2020.08396 ◽

2020 ◽

Vol 62 (3) ◽

pp. 1097-1107

Author(s):

R.Mythili ◽

P.Kalpana

Keyword(s):

Intrusion Detection ◽

Low Power ◽

Intrusion Detection System ◽

High Speed ◽

Detection System ◽

Network Intrusion Detection ◽

Content Addressable Memory ◽

Network Intrusion ◽

High Speed Network ◽

Network Intrusion Detection System

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LoRa-Based Smart IoT Application for Smart City: An Example of Human Posture Detection

Wireless Communications and Mobile Computing ◽

10.1155/2020/8822555 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Jinkun Han ◽

Wei Song ◽

Amanda Gozho ◽

Yunsick Sung ◽

Sumi Ji ◽

...

Keyword(s):

Smart City ◽

High Speed ◽

Detection System ◽

Low Cost ◽

Long Distance ◽

Sliding Windows ◽

Human Posture ◽

Artificial Intelligence Technology ◽

Posture Recognition

Scientists have explored the human body for hundreds of years, and yet more relationships between the behaviors and health are still to be discovered. With the development of data mining, artificial intelligence technology, and human posture detection, it is much more possible to figure out how behaviors and movements influence people’s health and life and how to adjust the relationship between work and rest, which is needed urgently for modern people against this high-speed lifestyle. Using smart technology and daily behaviors to supervise or predict people’s health is a key part of a smart city. In a smart city, these applications involve large groups and high-frequency use, so the system must have low energy consumption, a portable system, and a low cost for long-term detection. To meet these requirements, this paper proposes a posture recognition method based on multisensor and using LoRa technology to build a long-term posture detection system. LoRa WAN technology has the advantages of low cost and long transmission distances. Combining the LoRa transmitting module and sensors, this paper designs wearable clothing to make people comfortable in any given posture. Aiming at LoRa’s low transmitting frequency and small size of data transmission, this paper proposes a multiprocessing method, including data denoising, data enlarging based on sliding windows, feature extraction, and feature selection using Random Forest, to make 4 values retain the most information about 125 data from 9 axes of sensors. The result shows an accuracy of 99.38% of extracted features and 95.06% of selected features with the training of 3239 groups of datasets. To verify the performance of the proposed algorithm, three testers created 500 groups of datasets and the results showed good performance. Hence, due to the energy sustainability of LoRa and the accuracy of recognition, this proposed posture recognition using multisensor and LoRa can work well when facing long-term detection and LoRa fits smart city well when facing long-distance transmission.

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Study on the Precise Detection Method of Pavement Structural Depth

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1030-1032.2274 ◽

2014 ◽

Vol 1030-1032 ◽

pp. 2274-2278

Author(s):

Jian Feng Wang ◽

Fan Yang

Keyword(s):

High Speed ◽

Detection Method ◽

Detection System ◽

Low Cost ◽

High Accuracy ◽

Engineering Practice ◽

Important Indicator ◽

Key Factor ◽

Pavement Structure ◽

Detection Principle

Pavement structural depth is an important indicator of Pavement macro-structure. So how to use better method, with low cost to obtain the high accuracy of pavement structural depth indicators become the difficulty and key factor in road detection area.In this paper we propose a new detection pavement structure depth method.mainly studies the accurate detection principle of pavement structure depth, develops pavement structure depth detection system which can be used in engineering practice with high-speed, high-accuracy. making the detection of pavement structure depth more accurate and rapid.

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