Storage Performance Evaluation for IoT Gateway Implementation Using Raspberry Pi 2

IoT gateway is a core module exists in many of the IoT architectures that plays a role to connect WSNs to the internet, or specifically to the Cloud. However, conventional internet gateway is not sufficient to be IoT gateway. One of the most critical issue faced by IoT gateway is unstable internet connection especially when using cellular network. This work proposes that IoT gateway should have temporary storage to mask network issue. The objective of this work is to find out the most efficient solution for IoT gateway with temporary storage based on the elements of hardware, scheduler and storage method including database versus flat file on Raspberry Pi and NAND flash. From our experimental results, we found that the most efficient solution for temporary storage in IoT Gateway is using 4-threaded flat file I/O with Deadline scheduler

Measuring the accuracy of crowd counting using Wi-Fi probe-request-frame counting technique

Wi-Fi in smartphones are designed to periodically transmit probe-request-frame to determine when a known access point is within range and by capitalizing this Wi-Fi behavior, crowd counting and analysis have been done by continuous monitoring and counting these Wi-Fi frames. The proliferation of Wi-Fi enabled mobile devices and the ever-increasing number of mobile devices in use, suggests opportunities for developing lowcost crowd counting and analysis solution. This work attempt to measure how well do monitoring and counting these Wi-Fi frames correlate with the actual number of people presence in a crowd. In this paper, we also compare the pros and cons of various crowd counting technologies, describe the system that we used for counting Wi-Fi frames and compare its accuracy against manual crowd counting technique in an event involving the public continuously for 8 hours. The results are promising, the correlation between manual counting and Wi-Fi frames counting is 0.89322. In addition to that, the Wi-Fi frames counting technique can even reveal the retention rate of the crowd

Micro-Dispensing of Graphene Oxide Based Capacitive Tactile Sensors for Human Pressure-Pulse Detection

This paper reports a novel capacitive pressure-pulse sensor array based on drop-dispensed graphene oxide (GO) sensing elements. The utilization of drop dispensing technology enables us a low cost, flexible and precise method to fabricate multiple capacitive sensing elements. The printed droplets volume (GO aqueous dispersion) were around 33.5 to 65.4 pL with droplet diameter ranging 40 to 50um. The size (i.e., footprint and dielectric thickness) of a sensing element can be controlled by the total GO dispersed. In this paper, we report on the fabrication process and preliminary characterization of these printed GO capacitive sensors. Thus far, we have shown that these sensors have a sensitivity of ~10- 3 kPa- 1 , with a relative permittivity of the printed GO being ~6 to 7 (measured at a frequency of 600kHz). We have also demonstrated that the printed sensing elements can be used for human pulse sensing, which means that these sensors could potentially be used in wearable electronics and healthcare applications