Research of Panoramic Image Generation Using IoT Device with Camera for Cloud Computing Environment

Ahn, Hyochang; Lee, June-Hwan; Cho, Han-Jin

doi:10.1007/s11277-018-5972-2

Cited by 3 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The camera lens, with a horizontal field of view of 155 degrees, is connected to the Raspberry Pi through the camera serial interface (CSI). It captures video frames and these images are subsequently resized to a smaller size to facilitate faster transfer to the cloud [42]. These resized images are then transmitted to Firebase Storage, a cloud-based storage service, as depicted in Figure 8.…”

Section: Image Capturing and Output Feed: Iot And Cloudmentioning

confidence: 99%

An Assistive Model for the Visually Impaired Integrating the Domains of IoT, Blockchain and Deep Learning

Jadon,

Taluri,

Birthi

et al. 2023

Symmetry

View full text Add to dashboard Cite

Internet of Things, blockchain and deep learning are emerging technologies that have recently gained popularity due to their various benefits and applications. All three domains have had success independently in various applications such as automation, agriculture, travel, finance, image recognition, speech recognition, and many others. This paper proposes an efficient, lightweight, and user-friendly solution to help visually impaired individuals navigate their way by taking advantage of modern technologies. The proposed method involves the usage of a camera lens attached to a Raspberry Pi device to capture live video frames of the user’s environment, which are then transmitted to cloud storage. The link to access these images is stored within a symmetrical private blockchain network (no superior access), where all deep learning servers act as nodes. The deep learning model deployed on these servers analyses the video frames to detect objects and feeds the output back to the cloud service. Ultimately, the user receives audio notifications about obstacles through an earphone plugged into the Raspberry Pi. In particular, when running the model on a high-performing network and an RTX 3090 GPU, the average obstacle notification time is reported within 2 s, highlighting the proposed system’s responsiveness and effectiveness in aiding visually impaired individuals.

show abstract

Section: Image Capturing and Output Feed: Iot And Cloudmentioning

confidence: 99%

An Assistive Model for the Visually Impaired Integrating the Domains of IoT, Blockchain and Deep Learning

Jadon,

Taluri,

Birthi

et al. 2023

Symmetry

View full text Add to dashboard Cite

show abstract

“…This method aids reliable road planning and traffic management quality in smart cities. Ahn et al [37] introduced an image distribution method over IoT devices that addresses high-resolution image stitching issues. The load of the images is distributed to the cloud, from which the homographic information is fetched for exchange.…”

Section: Related Workmentioning

confidence: 99%

CMRS: A Classifier Matrix Recognition System for Traffic Management and Analysis in a Smart City Environment

et al. 2019

View full text Add to dashboard Cite

The application of the Internet of Things (IoT) in a smart city improves its efficiency in terms of communication and installation costs by scaling geographical distance through intelligent devices and digital information. Different applications in a smart city, including health care, road safety, industry and home automation, rely on the IoT. Considering the significance of the IoT in smart city road applications, this manuscript introduces a classifier matrix recognition system (CMRS) for improving realtime traffic optimization. This classifier matrix system performs an independent and matching analysis of the real-time traffic images and constructs a decision factor for deriving its conclusion. The conclusion is served as responding notifications through the connected IoT systems for the users employing roadsidecommunication-assisted applications. CMRS exploits the advantages of block classification and matrix operations for improving the correlation accuracy and similarity index. The experimental results indicate that the proposed CMRS improves correlation accuracy with a high similarity index and less processing time and dissimilarity rate. INDEX TERMS Block classification, image recognition, IoT, ITS, smart city, traffic management. I. INTRODUCTION The rapid development of the IoT is resulting in its services being used in different real-world applications. This communication platform is capable of connecting various elements, including humans, computers, machines, tiny sensors and other objects [1], [2]. More specifically, the connected devices are heterogeneous in nature, which facilitates pervasive access to resources, applications and services [3], [4]. The intelligence of the communicating devices in this paradigm provides anywhere and anytime access to resources the end user requests [5]. Because the interconnection of this platform incorporates heterogeneous devices, it supports various communication technologies ranging from device-todevice (D2D) to distributed cloud computing [6]. The independent operations of the devices are assisted via a wireless communication medium in which the protocol and technology are adopted appropriately. Distributed and concurrent The associate editor coordinating the review of this manuscript and approving it for publication was Chao Chen.

show abstract

Cloud Networking Computing

Kim

Manaligod

Lee³

et al. 2019

Wireless Pers Commun

View full text Add to dashboard Cite

Research of Panoramic Image Generation Using IoT Device with Camera for Cloud Computing Environment

Cited by 3 publications

References 20 publications

An Assistive Model for the Visually Impaired Integrating the Domains of IoT, Blockchain and Deep Learning

An Assistive Model for the Visually Impaired Integrating the Domains of IoT, Blockchain and Deep Learning

CMRS: A Classifier Matrix Recognition System for Traffic Management and Analysis in a Smart City Environment

Cloud Networking Computing

Contact Info

Product

Resources

About