scholarly journals Multi-Camera Vehicle Tracking Using Edge Computing and Low-Power Communication

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3334 ◽  
Author(s):  
Maciej Nikodem ◽  
Mariusz Słabicki ◽  
Tomasz Surmacz ◽  
Paweł Mrówka ◽  
Cezary Dołęga
Keyword(s):  
Embedded System ◽  
Low Power ◽  
Short Range ◽  
Vehicle Tracking ◽  
Radio Communication ◽  
Large Area ◽  
Camera Tracking ◽  
Graphic Processing Units ◽  
Detection And Tracking ◽  
Tracking Algorithms

Typical approaches to visual vehicle tracking across large area require several cameras and complex algorithms to detect, identify and track the vehicle route. Due to memory requirements, computational complexity and hardware constrains, the video images are transmitted to a dedicated workstation equipped with powerful graphic processing units. However, this requires large volumes of data to be transmitted and may raise privacy issues. This paper presents a dedicated deep learning detection and tracking algorithms that can be run directly on the camera’s embedded system. This method significantly reduces the stream of data from the cameras, reduces the required communication bandwidth and expands the range of communication technologies to use. Consequently, it allows to use short-range radio communication to transmit vehicle-related information directly between the cameras, and implement the multi-camera tracking directly in the cameras. The proposed solution includes detection and tracking algorithms, and a dedicated low-power short-range communication for multi-target multi-camera tracking systems that can be applied in parking and intersection scenarios. System components were evaluated in various scenarios including different environmental and weather conditions.

scholarly journals The Demonstration of S2P (Serial-to-Parallel) Converter with Address Allocation Method Using 28 nm CMOS Technology

2021 ◽  
Vol 11 (1) ◽  
pp. 429
Author(s):  
Min-Su Kim ◽  
Youngoo Yang ◽  
Hyungmo Koo ◽  
Hansik Oh
Keyword(s):  
Integrated Circuits ◽  
Embedded System ◽  
Low Power ◽  
High Speed ◽  
Cmos Technology ◽  
Clock Frequency ◽  
Clock Generation ◽  
Allocation Method ◽  
Evaluation Board ◽  
28 Nm

To improve the performance of analog, RF, and digital integrated circuits, the cutting-edge advanced CMOS technology has been widely utilized. We successfully designed and implemented a high-speed and low-power serial-to-parallel (S2P) converter for 5G applications based on the 28 nm CMOS technology. It can update data easily and quickly using the proposed address allocation method. To verify the performances, an embedded system (NI-FPGA) for fast clock generation on the evaluation board level was also used. The proposed S2P converter circuit shows extremely low power consumption of 28.1 uW at 0.91 V with a core die area of 60 × 60 μm2 and operates successfully over a wide clock frequency range from 5 M to 40 MHz.

The Development of Embedded System for Energy Saving in Electro-Hydraulic System

2013 ◽  
Vol 418 ◽  
pp. 63-69
Author(s):  
Sema Patchim ◽  
Watcharin Po-Ngaen
Keyword(s):  
Embedded System ◽  
Low Power ◽  
Hydraulic System ◽  
Fuzzy Controller ◽  
Low Cost ◽  
Operational Performance ◽  
Functional Design ◽  
Power Utility ◽  
Load Sensing ◽  
Oil Flow

In last decade, energy efficiency of hydraulic actuators systems has been especially important in industrial machinery applications [1-. And an advanced electronics world most of the applications are developed by microcontroller based embedded system. Energy processor based variable oil flow of hydraulic controller was presented to improve the efficiency of the motor by maintaining with the load sensing. These PIC processor combined with fuzzy controller were help to design efficient optimal power hydraulic machine controller. A functional design of processor and in this system was completed by using load sensing signal to control oil flow. The advantage of the proposed system was optimized operational performance and low power utility. Without having the architectural concept of any motor we can control it by using this method. This is a low cost low power controller and easy to use. The experiment results verified its validity.

A Low-Power Low-Cost 780MHz CMOS FSK Receiver for Short-Range Wireless Communication

2016 ◽  
Vol 25 (2) ◽  
pp. 220-226 ◽  
Author(s):  
Yadong Yin ◽  
Lihong Zhang ◽  
Yuanting Yang
Keyword(s):  
Wireless Communication ◽  
Low Power ◽  
Short Range ◽  
Low Cost

CenterTrack3D: Improved CenterTrack more Suitable for 3D Objects

2021 ◽  
pp. 1-32
Author(s):  
Lipeng Gu ◽  
Shaoyuan Sun ◽  
Xunhua Liu ◽  
Xiang Li
Keyword(s):  
Object Tracking ◽  
Research Field ◽  
Unmanned Vehicles ◽  
Current Frame ◽  
3D Objects ◽  
Detection And Tracking ◽  
Tracking Algorithms ◽  
Occluded Objects ◽  
Previous Frame ◽  
3D Information

Abstract Compared with 2D multi-object tracking algorithms, 3D multi-object tracking algorithms have more research significance and broad application prospects in the unmanned vehicles research field. Aiming at the problem of 3D multi-object detection and tracking, in this paper, the multi-object tracker CenterTrack, which focuses on 2D multi-object tracking task while ignoring object 3D information, is improved mainly from two aspects of detection and tracking, and the improved network is called CenterTrack3D. In terms of detection, CenterTrack3D uses the idea of attention mechanism to optimize the way that the previous-frame image and the heatmap of previous-frame tracklets are added to the current-frame image as input, and second convolutional layer of the output head is replaced by dynamic convolution layer, which further improves the ability to detect occluded objects. In terms of tracking, a cascaded data association algorithm based on 3D Kalman filter is proposed to make full use of the 3D information of objects in the image and increase the robustness of the 3D multi-object tracker. The experimental results show that, compared with the original CenterTrack and the existing 3D multi-object tracking methods, CenterTrack3D achieves 88.75% MOTA for cars and 59.40% MOTA for pedestrians and is very competitive on the KITTI tracking benchmark test set.

scholarly journals MULTI OBJECT DETECTION AND TRACKING USING OPTICAL FLOW DENSITY – HUNGARIAN KALMAN FILTER (OFD - HKF) ALGORITHM FOR VEHICLE COUNTING

2018 ◽  
Vol 11 (1) ◽  
pp. 17 ◽  
Author(s):  
Muhamad Soleh ◽  
Grafika Jati ◽  
Muhammad Hafizhuddin Hilman
Keyword(s):  
Kalman Filter ◽  
Object Detection ◽  
Optical Flow ◽  
Motion Blur ◽  
Research Topic ◽  
Vehicle Tracking ◽  
Flow Density ◽  
Illumination Change ◽  
Dynamic Background ◽  
Detection And Tracking

Intelligent Transportation Systems (ITS) is one of the most developing research topic along with growing advance technology and digital information. The benefits of research topic on ITS are to address some problems related to traffic conditions. Vehicle detection and tracking is one of the main step to realize the benefits of ITS. There are several problems related to vehicles detection and tracking. The appearance of shadow, illumination change, challenging weather, motion blur and dynamic background such a big challenges issue in vehicles detection and tracking. Vehicles detection in this paper using the Optical Flow Density algorithm by utilizing the gradient of object displacement on video frames. Gradient image feature and HSV color space on Optical flow density guarantee the object detection in illumination change and challenging weather for more robust accuracy. Hungarian Kalman filter algorithm used for vehicle tracking. Vehicle tracking used to solve miss detection problems caused by motion blur and dynamic background. Hungarian kalman filter combine the recursive state estimation and optimal solution assignment. The future positon estimation makes the vehicles detected although miss detection occurance on vehicles. Vehicles counting used single line counting after the vehicles pass that line. The average accuracy for each process of vehicles detection, tracking, and counting were 93.6%, 88.2% and 88.2% respectively.

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