Conference Papers

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    Modelling and analysis of lower metal on-chip interconnects using physical fabrication parameters
    (Institute of Electrical and Electronics Engineers Inc., 2019) Kulkarni, A.; Iteesh, V.A.; Sahith, S.R.
    This paper looks into the modelling and analysis of on-chip interconnects in the lower metal region of an Integrated Circuit (IC). A proposed π-interconnect model is quantitatively modelled and analysed and the delay time, td is used as a metric to measure performance change from ideal circuit simulations for varying interconnect lengths using a driver-load inverter pair. The π-model delay time performance is also compared with that of a layout of an driver-load inverter pair circuit and a 3-stage ring-oscillator circuit. The layout is generated using MOSIS SCMOS technology using ON Semiconductor C5 600nm device model with VDD = 5V. All modelling and analysis is done using open-source EDA tools and technology. © 2019 IEEE.
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    Mesh WSN data aggregation and face identification in fog computing framework
    (IEEE Computer Society help@computer.org, 2019) Sahith, S.R.; Rudraraju, S.R.; Negi, A.; Suryadevara, N.K.
    This work aims to aggregate data from various sensors in a mesh topology based Wireless Sensor Network (WSN). It analyzes this data using fog computing framework to trigger alerts. The WSN consists of nodes with several sensors like temperature sensor, potentiometer and light emitting diode connected with radio communication module XBee. The sensor nodes are connected in mesh topology for better reliability and using ZigBee protocol mechanism. The Fog gateway node collects the sensor data from several sensor nodes. The WSN also includes Pi Camera and passive infrared sensor augmented with Philips Hue Lights. Hue Light gives a visual indication of motion detection, using ON/OFF states. Pi camera captures image whenever any motion is detected. The captured images are used for face recognition by applying Eigenfaces method. The AI algorithm is applied on the aggregated temperature sensor data, at the Fog node level, to determine the adaptive threshold. If the temperature data from any sensor node is above the threshold value an alert message is triggered. The proposed system is run continuously for data collection and the functionality of the system is tested with various inputs and the results are encouraging. © 2019 IEEE.