In the existing Wireless Sensor Based Energy Conservation work, the communication protocol was limited to Bluetooth only which is very short distance and should require a device interface in order to view or control the data which is the drawback of the developed system.
The proposed Wireless Sensor Based Energy Conservation via Bluetooth work will include the low power high accuracy controllers through the Bluetooth communication as well we also control and view the data over the Intranet Network.
Load contains a Bulb, the current and Voltage consumed by the load will be monitored and an automated operation of the load based on PIR and LDR values will be done from remote location.
ARM11, PIR Sensor, LDR Sensor, Bluetooth module, Wi-Fi Router, 89s52, Current Sensor, Voltage Sensor, Relay Driver, Load.
OS: Embedded Linux, Language: C/ C++, IDE: Qt Creator.
Home automation, Industrial Power Control
Load Control, Remote location access,
In this Face Identification Implementation in a Standalone Embedded System paper is described an embedded system for face identification. The system, running on ARM processor, is built around BCM2835 processor and consists of several IP (Intellectual Property) modules designed as bus peripherals.
The face detection and recognition is accelerated with the help of a hardware and software algorithm modules. The system has been designed on the criteria of resources optimization, low power consumption and improved operation speed
The Existing work has been implemented on FPGA based processor device, which is complex and high cost of implementation when compared to an embedded chips. As well in the entire system description only procedure have been explained no exact output results where shown.
The host target for the proposed face detection system is an embedded environment based on ARM 11 architecture. Which has much higher RAM and Clock speech compared to an FPGA based Devices. Here using Raspbian Operating System, Open Computer Vision algorithm and Qt based GUI interface will be used to implement the face detection and recognition.
Whenever the authenticated face is identified the system will provided login access or else SMS will be sent to the concerned person with GPS location simultaneously a buzzer will be turned on to indicating the unauthorized entry.
ARM11, USB Camera, GSM, GPS, Buzzer, Power supply.
OS: Embedded Linux, Language: C/ C++, IDE: Qt Creator, Image Processing Algorithm.
Home, Security, Authentication sites
• Hand Held System and online face training can be done.
• Easy installation and usage
In this Human Data Interaction in IoT – The Ownership Aspect, we develop a password based user authenticated IoT device login server. This will provide the data access to the owner only.
The approach of the existing work has not been clearly explained, they not provide any practical approach for the data safety and security over the IoT application.
Proposed Human Data Interaction in IoT system will be implemented on a Operating System(OS) based interface, which included and advances speed processor architecture i.e ARM 11, which makes the system very robust and the networking over the internet is done through on board Ethernet module with built in web server.
Hardware: ARM11, Wi-Fi, Power supply, ADC, Sensors, Load.
Software: OS: Embedded Linux, Language: C/ C++, IDE: Qt Creator.
Applications: Automation, Educational Knowledge, Robotics.
- Helpful or the disable children and industrial automation for making daily activates, through controlling the devices over Internet.
In the A plug-n-play Internet enabled platform for Real time image processing existing system, they have used a Cellular based technology which is very unreliable for the image data transmission over the web. As the network speed is very less, so we cant observe the results at rapid speed.
Proposed A plug-n-play Internet enabled platform for Real time image processing System will be included with an advance algorithm based on Ethernet protocol, where will develop a server hosted on the raspberry pi board, and using Image processing algorithm the desired image will be processed and whenever the image processing is done immediately the results will be displayed on the webpage.
Raspbian OS, Opencv, web server
ARM 11(Raspberry pi), Ethernet router, USB camera
Web based results, Remote location accessing
Easy to access, live image feeding