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Wisenet


Published on Dec 02, 2015

Abstract

WISENET is a wireless sensor network that monitors the environmental conditions such as light, temperature, and humidity. This network is comprised of nodes called "motes" that form an ad-hoc network to transmit this data to a computer that function as a server.

The server stores the data in a database where it can later be retrieved and analyzed via a web-based interface. The network works successfully with an implementation of one sensor mote.

Introduction:

The technological drive for smaller devices using less power with greater functionality has created new potential applications in the sensor and data acquisition sectors. Low-power microcontrollers with RF transceivers and various digital and analog sensors allow a wireless, battery-operated network of sensor modules ("motes") to acquire a wide range of data. The TinyOS is a real-time operating system to address the priorities of such a sensor network using low power, hard real-time constraints, and robust communications.

The first goal of WISENET is to create a new hardware platform to take advantage of newer microcontrollers with greater functionality and more features. This involves selecting the hardware, designing the motes, and porting TinyOS. Once the platform is completed and TinyOS was ported to it, the next stage is to use this platform to create a small-scale system of wireless networked sensors.

System Description:

There are two primary subsystems (Data Analysis and Data Acquisition) comprised of three major components (Client, Server, Sensor Mote Network).

Primary Subsystems:

There are two top-level subsystems -

Data Analysis

Data Acquisition.

Data Analysis:

This subsystem is software-only (relative to WISENET). It relied on existing Internet and web (HTTP) infrastructure to provide communications between the Client and Server components. The focus of this subsystem was to selectively present the collected environmental data to the end user in a graphical manner.

Data Acquisition:

The purpose of this subsystem is to collect and store environmental data for later processing by the Data Analysis subsystem. This is a mix of both PC & embedded system software, as well as embedded system hardware. It is composed of both the Server and Sensor Mote Network components.

WISENET includes a socketed evaluation board (CC1010EB) and two evaluation modules (CC1010EM). The evaluation board provided access to all of the analog and digital pins on the CC1010, as well as two serial ports, a parallel programming port, RF network analysis ports, and other peripherals. Each evaluation module featured the CC1010, RF network hardware, an antenna port, and an analog temperature sensor. The modules connected to the evaluation board via two TFM-D sockets. These sockets also allowed the possibility of designing a custom expansion board.

WISENET is designed to measure light, temperature, and humidity. There are many digital temperature sensors available, but there is a much smaller selection of digital humidity and light sensors. A larger selection of analog sensors are available; however, analog sensors tended to require more power and be less precise than their digital counterparts, in addition to requiring more complex circuitry.

For these reasons, digital sensors are given higher priority. Two new sensors provided the required functionality. First, Sensirion released the SHT11, a digital temperature and humidity sensor with ultra low power consumption (550 MicroA while measuring, 1 MicroA when in sleep mode), a 14 bit analog to digital converter, and the desired accuracy (±5% relative humidity, ±3ºC). It also featured a simple serial interface.

The light sensor chosen was the Texas Advanced Optoelectonic Solutions (TAOS) TSL2550 ambient light sensor with SMBus interface. This sensor also featured ultra-low power (600 MicroA active, 10 MicroA power down), a 12-bit analog to digital converter, and dual photo diodes. The TSL2550 uses both photo diodes to compensate for infrared light and to produce a measurement that approximates the human eye response.














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