1BeaglePhone
BeaglePhone is experimental cape for developing analog
phone applications like VoIP gateway. This cape is based on Silicon Labs Si3215
ProSlic. The ProSLIC is a low-voltage CMOS device that provides a complete
analog telephone interface ideal for customer premise equipment (CPE)
applications.
BeaglePhone is chip-compatible with Asterisk PBX and can be
used for drivers developing.
This project is still under developing.
Planned features:
- FXO version of the cape
- Overvoltage/overcurrent protection
- Asterisk drivers
2.Traffic light controller
3.Streaming video beaglebone black
In this video, you look at video streaming (320x240,
640x480) using the Beaglebone black.
To realise this c language project i used: v4l driver, compression and
decompression JPEG, UDP protocol transfer, openCV image show.
4.Autonomous Solar Car
The aim of this project is to build a solar
energy powered autonomous car. Resistive matching has been employed to extract
maximum energy from a solar panel, with minimal complications. This is done in
order to maximize the amount of energy that is transferred from the solar cell
into a Li-ion battery. This battery is used to drive an H-bridge motor
controller which is controlled through the BeagleBone.
5.Building a Home Security System with BeagleBone
ne of the best kept secrets of the security industry is just
how simple the monitoring hardware actually is - BeagleBone has all the
computing power you need to build yourself an extremely sophisticated access
control, alarm panel, and home automation and network intrusion-detection
system. Security companies make a fortune each year by charging exorbitant fees
to their customers. You will learn how easy it is to make an alarm system with
Beaglebone.
6.BeagleBone Home Automation
Home automation lets you control daily activities such as
changing the temperature, opening the garage door, or dimming the lights of
your house using microprocessors. BeagleBone is a low-cost, high-expansion,
hardware-hacker-focused BeagleBoard. It is small and comes with the
high-performance ARM capabilities you expect from a BeagleBoard. BeagleBone
takes full-featured Linux to places it has never gone before.
Starting with the absolute basics, BeagleBone Home Automation
gives you the knowledge you will require to create an Internet-age home
automation solution. This book will show you how to set up Linux on BeagleBone.
You will learn how to use Python to control different electronic components and
sensors to create a standalone embedded system that also accepts control
remotely from a smartphone.
This book starts with the very basics of Linux administration
and application execution using terminal connections. You will learn the basics
of the general purpose input/output pins and discover how various electronic
sensors and electronic components work. The "hardware jargon" is
explained, and example applications demonstrating their practical use are
created so that you will feel in control of the capabilities provided.
Network programming is also a big part of this book, as the
created server will be made accessible from the Internet through a smartphone
application. You will also learn how to create a fully working Android
application that communicates with the home automation server over the
Internet.
7.Application of image processing techniques for the extraction of vehicle
number plates over ARM target board
Correct recognition of vehicles violating traffic rules and
regulations is a major challenge in the present complex traffic environment.
Automatic Number Plate Recognition (ANPR) systems plays an important role in
the detection of such events. ANPR systems are typically standalone systems
using the capabilities of embedded processors for correct recognition. The
limited processing capabilities hinders the efficient determination of location
of number plates in such images satisfying the real time criteria. This paper
presents an adopted method for the image preprocessing, image detection and
extraction of standardized white background vehicle number plates. Application
of suitable Gaussian Filters along with other image preprocessing techniques,
Binary jumps and Image differencing techniques have been carried out in this
work. An ARM Cortex A8 processor with 1GHz processor and 512 MB RAM has been
selected as the candidate embedded processor in this work. Experiments show
that the proposed method posses over 90% accuracy.
8.Design of multi-threaded real time embedded video acquisition system from
IP cameras
IP cameras have become the de facto imaging sensor used for
video acquisition in surveillance systems because of its advantages over
traditional analog cameras. Video Compression schemes are adopted for efficient
transmission and bandwidth preservation of the link. Currently H.264 is the
compression standard adopted for video compression in these devices. Logging of
the videos from the imaging sensors is the fundamental responsibility of these
surveillance systems. This paper presents an efficient method for the multi
threaded acquisition of H.264 encoded video stream from these imaging sensors.
An embedded implementation of the proposed method have also been carried out on
an ARM Cortex A8 target. The embedded system developed possesses the
capability of acquiring compressed video streams concurrently from 4 IP Cameras
while handling the real time processing constraints.
9.A cloud computing-based image codec system for lossless compression of
images on a Cortex-A8 platform
Aimed to provide an efficient architecture for the storage
and processing of medical images, a cloud computing-based system is proposed in
this paper. In addition, with the highly increased computational ability of
embedded systems, an ARM-based Cortex-A8 embedded platform is applied in the proposed
architecture as the kernel for the lossless compression, decompression, as well
as the processing of medical images. All the images generated are first sent to
the embedded platform for lossless compression before stored in the image
database server. On the other hand, images are retrieved and first sent to the
platform for decompression, and then transmitted via the network to the client
for viewing purpose. In the proposed system, the decompressed images are
transmitted with the protocol of HTTP, which means only a browser is needed for
the client. Moreover, the client can perform image processing, e.g, image
sharpening and histogram equalization with respect to the selected image in the
browser, no other application program is required. As no other application
program is required for the client other than the browser, the proposed system
architecture is very easy to maintain with, and the computational burden
traditionally imposed on the client can be quite alleviated. Furthermore, the
coding algorithm used is very effective and efficient for the lossless
compression of images as we will see in the experiment. The cloud
computing-based architecture in conjunction with the high efficient coding
algorithm make the proposed system very feasible for practical usage.
10.The Challenge of Testing the ARM CORTEX-A8/sup TM/ Microprocessor Core
The DFT and test challenges faced, and the solutions
applied, to the Cortex-A8
microprocessor core are described in this paper. New DFT techniques have been
created to address the challenges of distributing a DFT core solution that
ultimately end up in many different environments. This core comprises
synthesized, hand-mapped, hand-placed (HMHP) and custom blocks. A DFT solution
had to be created that could be utilized by a multitude of customers
11.Temperature controlling system for LED lighting based on ARM
Since LEDs are generally considered to be an important
lighting source of the future, an ARM-based LED
intelligent lighting system was provided in this paper. According to the
ambient temperature obtained by sensors, the designed system can adjust the
glow color automatically to provide a pleasant lighting environment. Based on
the ARM Cortex-M0
processor, the hardware and software of this system were accomplished and a
series of pulse width modulation signals were generated to drive the LEDs. The
testing results of the physical prototype show that the designed system works
well. Thus, the preliminary research proves the possibilities of smart
lighting.
12.Smart home design based on ZigBee wireless sensor network
is work is based on the Internet of Things and ZigBee
wireless sensor network technology. A kind of smart home design based on ZigBee
wireless sensor network was proposed in this paper. Texas Instruments MCU
device LM3S9B96, which is the ARM Cortex-M3 based controllers, was used in this system. The
entire system is running on the μC/OS-II embedded real-time multitasking
operating system. Users can access this system by a dynamic webpage of LwIP
TCP/IP protocol stack or GSM SMS. Using this system users can conveniently know
the environment parameters of home, such as temperature, humidity, meter
readings, light, and control the home electronic equipments, such as light,
aircondition, heater, by ZigBee wireless sensor network.
13.On-line monitoring system of insulator leakage current based on ARM
A ceramic insulator has an excellent anti-pollution
performance, but sometimes flashover occurs on it and then the outage of power
network follows. This paper analyzes the formation mechanism of flashover and
the result is that the RMS of leakage current(LC) and discharge pulses reflect
the contamination severity approximately. This shows that to a large extent the
flashover accident can be avoided by means of monitoring the leakage current
value and the discharge pulses. Existing monitoring device for contaminated
insulators inspects either leakage currents or discharge pulses, also, it is
difficult to meet the requirements of the client for low-power consumption, low
cost and high reliability. In this paper, a novel low-power and low-cost online
monitoring system is presented, which is based on ARM
Cortex-M and Zigbee wireless network. In addition,
the monitoring system not only acquires the leakage current and discharge
pulses of insulator strings, but also measures the environmental temperature
and humidity and then comprehensively analyzes the severity of insulator
pollution. After that the results will be displayed on the LCD or sent to the
control center through the Zigbee network. Tests show that the monitoring
system has good accuracy and good practical performance.
Brain EEG signal processing for controlling a robotic
arm
Researchers recently proposed new scientific methods for
restoring function to those with motor impairments. one of these methods is to
provide the brain with a new non-muscular communication and control channel, a
direct Brain-Machine Interface (BMI). This paper presents a Brain Machine
Interface (BMI) system based on using the brain electroencephalography (EEG)
signals associated with 3 arm movements (close, open
arm and close hand) for controlling a robotic arm. Signals recorded from one subject using Emotive Epoc
device. Four channels only were used, in our experiment, AF3, which located at
the prefrontal cortex and F7, F3, FC5 which located
at the supplementary motor cortex of the brain.
Three different techniques were used for features extraction which are: Wavelet
Transform (WT), Fast Fourier Transform (FFT) and Principal Component Analysis
(PCA). Multi-layer Perceptron Neural Network trained by a standard back
propagation algorithm was used for classifying the three considered tasks.
Classification rates of 91.1%, 86.7% and 85.6% were achieved with the three
used features extraction techniques respectively. Experimental results show
that the proposed system achieved high classification rates than other systems
in the same application.
Implementation of a Web of Things based Smart Grid to
remotely monitor and control Renewable Energy Sources
This paper describes a Smart Grid architecture implemented
with the help of Web of Things. Web of Things comprise of a set of Web services
provided on top of a number of Internet enabled Embedded devices. The Web
browser on any computer can act as an interface to the services provided by
these Web of Things. The Embedded devices are ARM Cortex M3 Processor based devices with Ethernet
capabilities. CMSIS Real Time Operating System is used for process control on
each of these embedded devices. LwIP Protocol Stack is implemented on top of
each of these devices so that IP connectivity can be established. The Web
interfaces provide us real time information on each of the energy meters that
are installed on site and communicate to the Embedded Internet devices using
MODBUS communication protocol. Real Time energy source scheduling, energy
source selection, power connection and disconnection are some of the services
that are provided to an on-line authenticated user. The Embedded Systems lab
Infrastructure at the TIFAC CORE for 3G/4G Communication at National Institute
of Science and Technology was used for the hardware testing of the embedded
modules. We were greatly helped by the Software developers at NIST Technology
Consultancy Services in designing the web applications and interfaces for our
Web of Things architecture.
Embedded System for Biometric Online Signature
Verification
This paper describes the implementation on
field-programmable gate arrays (FPGAs) of an embedded system for online
signature verification. The recognition algorithm mainly consists of three stages.
First, an initial preprocessing is applied on the captured signature, removing
noise and normalizing information related to horizontal and vertical positions.
Afterwards, a dynamic time warping algorithm is used to align this processed
signature with its template previously stored in a database. Finally, a set of
features are extracted and passed through a Gaussian Mixture Model, which
reveals the degree of similarity between both signatures. The algorithm was
tested using a public database of 100 users, obtaining high recognition rates
for both genuine and forgery signatures. The implemented system consists of a
vector floating-point unit (VFPU), specifically designed for accelerating the
floating-point computations involved in this biometric modality. Moreover, the
proposed architecture also includes a microprocessor, which interacts with the
VFPU, and executes by software the rest of the online signature verification
process. The designed system is capable of finishing a complete verification in
less than 68 ms with a clock rated at 40 MHz. Experimental results show that
the number of clock cycles is accelerated by a factor of ×4.8 and ×11.1, when
compared with systems based on ARM Cortex-A8 and when substituting the VFPU by the
Floating-Point Unit provided by Xilinx, respectively.
A Multi-camera Wireless Capsule Endoscopic System
The aim of this project is to build an efficient multi
camera wireless capsule endoscopic system, thereby trying to make the capsule
have 360° angle of view. The primary idea is to address the problem of limited
diagnosis caused due to the formation of blind areas while using a single
camera. A multi camera approach helps to reduce the blind area. However
increased image sensors cause increase in power consumption. In this work, a 4
camera wireless capsule system prototype was built which uses JPEG image
compression to reduce the data size needed to be transmitted by the RF
transmitter. Stellar is LM4F120 (ARM Cortex M4) micro controller performs the main task of
image compression, EZ430-RF2500 to establish the wireless link and the cameras
used are Omni vision's OV7760.
Development of Telugu Text to Speech System Using OMAP
3530
Speech is the important mode of communication. Speech
synthesis is the artificial production of human speech. A text to speech system
is to convert an arbitrary text into speech .In India different languages have
been spoken each being the mother tongue of tens of millions of people. This
text to speech sytem is primarily developed for Telugu, a Dravidian language
predominantly spoken in Indian state of Andhra Pradesh where it is an official
language. Telugu TTS has to face many challenges during the conversion of text
to speech.The most important qualities expected from this system are
naturalness and intelligibility. This paper describes a development of a Telugu
text to speech system using concatenative synthesis method using beagle board
OMAP 3530(ARM Cortex A-8
core) in linux.
Robotic Valet Parking System
Due to influx of vehicles on the road, citizens inevitably
combat traffic congestion on a daily basis. This is underlined by the lack of
parking infrastructure and shoot up of vehicle to human population ratio. The
Robotic Valet Parking System uses the robotic valets, which are the vehicle
carriers and parks the vehicles compactly in a given space of the parking area
once the driver loads his vehicle at the loading bay. Robotic Valet Automated
Parking System (APS) provides solution for the parking problems without the
need for special construction for automation. The conventional concrete garages
can be transformed into an automated parking system with the use of robotic
valets. Since the robotic valet APS requires concrete flooring, which provides
the fire separation, builders consider it approvable. The number and the
position of the occupied vehicles can be determined without the deployment of
the sensors in each of the parking slots. The vacancy of the parking garage is
displayed on the LCD screen which is of benefit to the costumer. The central processing
unit wirelessly controls the locomotion of robotic valets and the arrangement
of vehicles in the parking area. We shall prove the space efficiency, accuracy,
operational speed, safety and cost effectiveness of the proposed parking
system. A functional prototype of a robotic valet is built which parks the
vehicle loaded. The Unified Technology Learning Platform (UTLP) Kit, which has
TI (Texas Instruments) ARM CORTEX
A-8 microprocessor unit embedded in the TI OMAP 3530 applications processor, is
the control unit and this monitors the movement of the robotic valet
wirelessly. On producing the parking slip at the exit the robotic valet
automatically retrieves the vehicle to the costumer.
Software-defined Radio based On Cortex-A9
This paper presents an implementation of Software-defined
Radio (SDR) system over ARM Cortex-A9
processor. Compared with conventionally used general purpose CPU, e.g. X86 CPU,
ARM processors have advantages in both price and
power consumption under the same computing capability. Two basic issues of SDR
over ARM are investigated: the real-time operation
and signal processing efficiency. For the former issue, we select the
Linux-based real-time operating system Xenomai, which is built on Cortex-A9 platform. Testing results show that the
performance of Xenomai on Cortex-A9 meets the
real-time requirement of SDR. Furthermore, the NEON technology of Cortex-A9 is used to optimize the complex signal
processing algorithms in communication systems. Soft Demodulation is taken as
an example for the optimization, and the experimental results are provided to
show the improvement of signal processing efficiency.
