Abstract-A ZigBee based wireless sensor network is implemented in this paper which is of low-cost solar-powered air quality monitoring system. The main objective of the proposed architecture is to interfacing various sensors to measure the sensor analog data and displayed in LabVIEW on the monitor using the graphical user interface (GUI). The real time ambient air quality monitoring in smart cities is of greater significance for the health of people. The wireless network sensor nodes are placed at different traffic signals in the smart cities which collect and report real-time data on different gases which are present in the environment such as carbon monoxide (CO), nitrogen dioxide (NO 2), methane (CH4) and humidity. The proposed system allows smart cities to monitor air quality conditions on a desktop/laptop computer through an application designed using graphical programming based LabVIEW software and provides an alert if the air quality characteristics exceed acceptable levels. The sensor network was successfully tested on the campus of the institute of aeronautical engineering, Hyderabad. The sensor data are indicated by different indicators on the front panel of LabVIEW and also different charts are plotted with respect to time and amplitude which explains the severity of polluted areas.

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Abstract-A remote monitoring and control are one of the most important criteria for maximizing the production in any industry. With the development of modern industry the requirement for industrial monitoring system is getting higher. This project explains the real time scenario of monitoring temperature and humidity in industries. National Instruments my RIO is used and results are observed on LabVIEW front panel and VI Server. The server VI program and client VI program is developed in block diagram for the two sensor data. This proposed system develops a sensor interface device essential for sensor data acquisition of industrial Wireless Sensor Networks (WSN) in Internet of Things (IOT) environment. By detecting the values of sensors like temperature, humidity present in the industrial area. The results are displayed on the web page. The data can be accessed with admin name and password. After logging into the web page the index of files is displayed. After restarting the my RIO kit and initiate the deploying process the file the excel sheet will appear on the VI Server. This VI server is tested for its working, using a data acquisition web application using a standard web browser. The critical situation can be avoided and preventive measures are successfully implemented.

<p>All the devices are interconnected each other in digital form, for different applications the input data is encoded for error correcting and detecting purpose. The paper describes the transmission of QAM signals with two level encoded stages, i.e. convolutional and hamming coded GFDM system with 256-point IFFT at transmitter and FFT at the receiver using LABVIEW software. GFDM is a non-orthogonal, digital multicarrier transmission scheme which digitally implements the classical filter bank approach. GFDM transmits a block of frame composed by M time slots with K subcarriers. The higher order QAM is used because of transmitting more data but is less reliable when compared to lower order QAM. Based on GFDM specifications for the IEEE 802.11, latest 5G physical layer standards, the coding is provided by ½ rate encoder at the input side, and Maximum Likelihood decoder at the receiver side is used. The standard convolution code (7, [171, 133]), is used as encoder for the GFDM system. The GFDM complex values are displayed in the front panel, along with FFT and power spectrum is plotted for GFDM signal. The array of input bits and output bits are shown with green colour LED’s. The van de Beek algorithm is used at the receiver for maximum likelihood detection acts as convolutional decoder of GFDM signal. Next the signal is subjected to remove cyclic prefix and zero padding and applied to channel estimation algorithm. The un-equalized data and equalized data graph is shown in the front panel, before and after channel estimation VI. With BER VI available in the LABVIEW the data is normalized and its response is plotted with respect to SNR. BER values for different levels of encoders have shown in table for SNR values. This paper concludes the 32.91% improvement in BER for two levels of concatenated codes.Thus the GFDM signal outperforms the OFDM signal interms of BER for series levels of coding using labVIEW software.</p>