IoT
This report presents an end-to-end methodology for collecting datasets to recognize handwritten English alphabets in the Indian context by utilizing Inertial Measurement Units (IMUs) and leveraging the diversity present in the Indian writing style. The IMUs are utilized to capture the dynamic movement patterns associated with handwriting, enabling more accurate recognition of alphabets. The Indian context introduces various challenges due to the heterogeneity in writing styles across different regions and languages.
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The Internet of Things (IoT) is the nova emergence of connecting devices, people, and objects over the internet as sensors and actuators for a targeted application. Among popular IoT applications, location based IoT services are curtailed. Where the geographical location of a moving object will be estimated based on signal strength values using algorithms. To estimate the locations using algorithms distance measurement such as Received Signal Strength Indicator (RSSI) is required.
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The project research team successfully established China's first Inertial Motion Tracking Dataset (IMTD), which can be widely used for artificial intelligence model training in fields such as satellite-free navigation, unmanned driving, and wearable devices. Based on the IMTD dataset, the motion tracking method proposed by Wang Yifeng, Zhao Yi, and others breaks through the limitations of traditional motion tracking and positioning technologies such as inertia, optics, GPS, and carrier phase.
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333 Views
We introduce a high-performance computer vision based Intraveneous (IV) infusion speed measurement system as a camera application on an iPhone or Android phone. Our system uses You Only Look Once version 5 (YOLOv5) as it was designed for real-time object detection, making it substantially faster than two-stage algorithms such as R-CNN. In addition, YOLOv5 offers greater precision than its predecessors, making it more competitive with other object detection methods.
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Smart homes contain programmable electronic devices (mostly IoT) that enable home automation. People who live in smart homes benefit from interconnected devices by controlling them either remotely or manually/autonomously. However, high interconnectivity comes with an increased attack surface, making the smart home an attractive target for adversaries. NCC Group and the Global Cyber Alliance recorded over 12,000 attacks to log into smart home devices maliciously. Recent statistics show that over 200 million smart homes can be subjected to these attacks.
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This dataset provides valuable insights into hand gestures and their associated measurements. Hand gestures play a significant role in human communication, and understanding their patterns and characteristics can be enabled various applications, such as gesture recognition systems, sign language interpretation, and human-computer interaction. This dataset was carefully collected by a specialist who captured snapshots of individuals making different hand gestures and measured specific distances between the fingers and the palm.
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1049 Views
Abstract—This paper presents a novel approach to optimizing resource allocation in Internet of Things (IoT) networks, focusing on enhancing energy efficiency (EE) while maintaining age of information (AoI) awareness through device-to-device (D2D) communication. Our proposed solution integrates simultaneous wireless information and power transfer (SWIPT) with energy harvesting (EH) techniques. Specifically, D2D users employ time switching (TS) to harvest energy from the environment, while IoT users utilize power splitting (PS) to obtain energy from base stations (BS).
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779 Views
Over 34,000 frames from 60 commercial-off-the-shelf ZigBee devices were collected in various scenarios including indoor/outdoor and line-of-sight/non-line-of-sight (LOS/NLOS). The ZigBee devices are hybrid, with 36 equipped with power amplifiers and the other 24 not. The ZigBee device uses the CC2530 chip, while the power amplifier is the RFX2401C chip. The signal frames in each scenario are placed in a separate folder, where all device numbers are fixed. Each frame reaches its maximum length, which includes 266 symbols.
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619 Views