Live Video Streaming Research Articles

What is the educational value and clinical utility of artificial intelligence for intraoperative and postoperative video analysis? A survey of surgeons and trainees.

Surgical complications often occur due to lapses in judgment and decision-making. Advances in artificial intelligence (AI) have made it possible to train algorithms that identify anatomy and interpret the surgical field. These algorithms can potentially be used for intraoperative decision-support and postoperative video analysis and feedback. Despite the very early success of proof-of-concept algorithms, it remains unknown whether this innovation meets the needs of end-users or how best to deploy it. This study explores users' opinion on the value, usability and design for adapting AI in operating rooms. A device-agnostic web-accessible software was developed to provide AI inference either (1) intraoperatively on a live video stream (synchronous mode), or (2) on an uploaded video or image file (asynchronous mode) postoperatively for feedback. A validated AI model (GoNoGoNet), which identifies safe and dangerous zones of dissection during laparoscopic cholecystectomy, was used as the use case. Surgeons and trainees performing laparoscopic cholecystectomy interacted with the AI platform and completed a 5-point Likert scale survey to evaluate the educational value, usability and design of the platform. Twenty participants (11 surgeons and 9 trainees) evaluated the platform intraoperatively (n = 10) and postoperatively (n = 11). The majority agreed or strongly agreed that AI is an effective adjunct to surgical training (81%; neutral = 10%), effective for providing real-time feedback (70%; neutral = 20%), postoperative feedback (73%; neutral = 27%), and capable of improving surgeon confidence (67%; neutral = 29%). Only 40% (neutral = 50%) and 57% (neutral = 43%) believe that the tool is effective in improving intraoperative decisions and performance, or beneficial for patient care, respectively. Overall, 38% (neutral = 43%) reported they would use this platform consistently if available. The majority agreed or strongly agreed that the platform was easy to use (81%; neutral = 14%) and has acceptable resolution (62%; neutral = 24%), while 30% (neutral = 20%) reported that it disrupted the OR workflow, and 20% (neutral = 0%) reported significant time lag. All respondents reported that such a system should be available "on-demand" to turn on/off at their discretion. Most found AI to be a useful tool for providing support and feedback to surgeons, despite several implementation obstacles. The study findings will inform the future design and usability of this technology in order to optimize its clinical impact and adoption by end-users.

Video, talk and text: How do parties communicate coherently across modalities in live videostreams?

This study explores how participants co-accomplish coherence in multi-modal conversation. We observed online watch parties, with an interest in the intertwining of text, talk and video. The data comes from two different communities on the live-streaming platform Twitch.tv. Each community consists of one live-streamer and their viewership. The live-streamers broadcast an audio-visual artifact, while simultaneously communicating with their viewers in real-time. The two were highly interactive, despite one (the streamer) speaking and reading, and the other (the chatters) typing and listening. The crisscross of modalities introduces challenges for the management and intelligibility of conversation. One coherence strategy involved a 4-stage process whereby streamers redirected viewers’ attention, and then initiated a collaborative activity. This 4–stage sequence illustrates a predictable structure that is potentially applicable to other digital & multimodal environments. Methodological challenges of digitally-mediated interaction are addressed, such as transcription of voice-and-text cross-modal conversation.

Smart Journalism

Journalism is an essential system in this modern era. In this project entitled “Smart Journalism” is trying to build up a SaaS based application that would help a journalist to adapt to their surroundings; record telephone interviews, record live events audio video streams capture pictures etc. This is a perfect tool for a journalist in breaking news situations. The job often in cludes working odd or irregular hours and travelling to conduct research or interviews. Some reporters also put themselves in dangerous situations, such as disaster sites or war zones, in order to get a story. In such situations Journalists can report the admin in any emergency situations. SaaS based concept is been implemented in this project via giving all the Media Admins to safely register over the system “Smart Journalist” where they have to select the plan which helps in adding the number of post they want to post in this application, After Successful registration of Media Admin, MA is used to create a profile for the journalist specifying the current media and thus generating a ID which uniquely identifies each of the Journalist from other Media Admins. An ID card and login detail is generated and emailed to the journalist. From which journalist is to login and create New Post with uploading images, audi os, videos, text etc. according to news category. Which once submitted by the Journalist is analyzed by the Media Admin for Approval, after Approval the Post is shared to the common user page created by the Media Admin with a specific design. Usually, some Journalists sometimes put themselves in dangerous situations to cover the breaking news. In such situations they can also state the message about the situation by which the Media Admin can manage & overcome the situations. The website utilizes various technologies and frameworks such as React, NodeJS, Express, MongoDB

Fleet: Improving Quality of Experience for Low-Latency Live Video Streaming

Low-latency live video streaming proposes more challenges on designing Adaptive Bit Rate (ABR) algorithms than video-on-demand streaming. In this paper, we present Fleet, a solution that improves user quality of experience (QoE) in terms of video quality, video switches, video freezes, and latency. Fleet is designed to meet two operational challenges at the same time: (1) optimizing QoE under dynamic mobile network conditions and (2) ensuring a low latency experience with minimal visual quality degradation. The core of Fleet is a stochastic model predictive controller that incorporates network conditions and client states for bitrate adaptation. The idle period problem presents great challenges for bandwidth measurement and client state prediction. Fleet consists of an HTTP chunk level bandwidth measurement algorithm, and a practical live video streaming evolution model for client state prediction. Besides, a throughput probability predictor is trained to capture the mobile network’s uncertainty. And, a triple threshold playback speed controller is designed for latency management. Fleet is practically implemented in dash.js and evaluated over both synthetic and real-world mobile network conditions. Our study shows that compared with the state-of-the-art solution, Fleet achieves an average QoE improvement of 39.7% and 37.9%, respectively. Moreover, Fleet has a good generalization, outperforming existing algorithms even on new video traces and network conditions.

Real-Time Intersection Vehicle Turning Movement Counts from Live UAV Video Stream Using Multiple Object Tracking

Real-Time Intersection Vehicle Turning Movement Counts from Live UAV Video Stream Using Multiple Object Tracking

Prioritizing protection communication in a 5G slice: Evaluating HTB traffic shaping and UL bitrate adaptation for enhanced reliability

Abstract5G network slicing is promising in prioritizing time‐critical protection communication in wireless networks of smart grids. However, network slicing offered by telecommunication providers encompasses all smart grid applications, lacking granularity. Smart grid automation standards provide recommendations on prioritization of protection communication to improve reliability but only for wired connections. Therefore, this paper investigates hierarchical token bucket (HTB) traffic shaping and uplink (UL) bitrate adaptation of a live video stream for prioritizing protection communication within a 5G slice. An experimental setup combines controller‐hardware‐in‐the‐loop (CHIL) with a quality of service (QoS) measurement system for validation. The system under test consists of commercial 5G networks, intelligent electronic devices (IEDs), and merging units for validation with three smart grid applications: fault location, line differential, and intertrip protection. HTB traffic shaping improves protected faults by 47.57% in congested and 1.16% in non‐congested scenarios. UL bitrate of the video stream adaptation by 2 Mbps increases protected faults by 3.69%. HTB traffic shaping even improves prioritization with a wired connection without introducing additional delays. HTB traffic shaping must be deployed in routers to maintain good QoS for critical applications. Collaboration between utilities and telecommunication providers is essential to effectively deploy 5G network slicing on smart grids.

A DASH server-side delay-based representation switching solution to improve the quality of experience for low-latency live video streaming

This work addresses the integration of real-time transmission systems, including IP cameras and production systems (like OBS or vMix), that use protocols such as RTSP (Real Time Streaming Protocol) or SRT (Secure Reliable Transport), with content distribution technology based on LL-DASH (Low Latency DASH -Dynamic Adaptive Streaming over HTTP-), taking advantage of the fact that DASH offers significant well-known advantages for content distribution over the Internet and via CDNs (Content Delivery Networks). Considering the limitations of the LL-DASH standard regarding the adaptation to network conditions, this paper proposes a new solution called Server-Side Representation Switching (SSRS). SSRS uses an approach based on the server measuring the delay in the requests made by clients, whose variation may be due to a decrease in bandwidth, as occurs in Wi-Fi networks with a high number of clients. To evaluate the effectiveness of the proposed solution, a testbed has been developed that allows the performance evaluation of both the LL-DASH system and the solution based on server-side decision-making. In addition, the developed solution has been compared with known algorithms (L2A and LoL+) integrated into the Dash.js player. The results show that the Server-Side Representation Switching solution offers a good trade-off between the transmitted quality and the final delay measured at the client, compared to the other algorithms evaluated. Moreover, it holds the advantage of being straightforward to implement and does not require any modifications to the players used.• Networks • Network performance evaluation • Network performance analysis.

An online virtual laboratory model based on the Internet of Things for use in the field of renewable energy

The field of engineering has always relied on experimentation as a pillar to deepen students' knowledge. During the period of the Corona pandemic, the importance of remote laboratories emerged as universities closed their doors due to this pandemic. From here came the idea of the research, which is the design and implementation of a prototype remote laboratory suitable for conducting practical experiments based on Internet of Things (IoT) technique. The proposed remote laboratory is based on a client-server model; where the server side represents the laboratory side, and the client side represents users, which are divided into three user types: administrators, lecturers, and students. The proposed experiments are based on the Effects of various environmental parameters on PV-module power and efficiency. Students can access it in a secure way through an interface that is provided as a web page, and all that users need to perform the experiment is a web browser, internet connection, username and password. The low-cost Hardware part involves the Microcontroller, the solar cell, and the sensors that are required for data acquisition from the overall experiment environment, in addition to actuators to control the environmental parameters. The hardware part is designed to be controlled by software, which has been created in several programming languages (Python, HTML, JavaScript, MySQL, and LabVIEW). Finally, a Web camera was connected to the server to provide a live video stream to monitor the device's status to give the student the feeling that he is close to the real laboratory. Finally, the proposed system supported with automatic assessment mechanism to evaluate the student's performance during the conduction of the experiment and thus to reduce the effort of the supervisor of the laboratory.

Learning from a live stream: Differences in motivations, psychological needs, perceived learning, and information behaviors across live streaming and nonlive social media video viewing.

Learning from a live stream: Differences in motivations, psychological needs, perceived learning, and information behaviors across live streaming and nonlive social media video viewing.

Supplemental Material for Learning from a live stream: Differences in motivations, psychological needs, perceived learning, and information behaviors across live streaming and nonlive social media video viewing.

Supplemental Material for Learning from a live stream: Differences in motivations, psychological needs, perceived learning, and information behaviors across live streaming and nonlive social media video viewing.

A Narrative Inquiry of Live Video Streaming: Voices of EFL Teachers to Reflect on Their Online Learning

Despite being widely investigated by previous studies in online learning, live video streaming (LVS) as a strategy for teaching English as a foreign language receives scanty attention. The present narrative inquiry aims to showcase an empirical insight into how live video streaming on Facebook is organized in online learning to fill this void. Two EFL teachers of a senior secondary school in Central Java, Indonesia, volunteered to participate in this study. Data were garnered through interviews and classroom observation. The data were analyzed using thematic analysis. The study’s findings demonstrated that teaching through LVS on Facebook assisted EFL teachers in managing their online learning. The LVS-mediated learning process portrayed teaching, social, and cognitive presence during online learning. This result indicates that the learning platform provides promising prospects for teachers to optimize online English-speaking courses. The study also explored several challenges the EFL teachers encounter when managing LVS in their online classes with material and media preparation, time allocation, and internet connection. This study concludes with some pedagogical implications for how a teacher as a curriculum designer engages students in learning English and empowers them in online learning.

Pengaruh Live Streaming Video Promotion, Diskon Harga, Online Costumer Review Saat Live Streaming Tiktok Terhadap Keputusan Pembelian

The purpose of this study is to determine the effect of live streaming video promotion, price discounts and online customer reviews when live streaming Tiktok on purchasing decisions. This research method uses quantitative methods with data analysis using instrument data tests, classical assumption tests, and multiple linear regression analysis using the SPSS application. The sampling method used is non-probability sampling with purposive samp ling techniques. The number of samples obtained by 140 respondents who had shopped through Tiktok live streaming in Solo Raya. The results of this study show that the variables of the influence of live streaming video promotion, price discounts and online customer reviews have a significant partial effect on purchasing decisions on Tiktok live streaming. While the variables The influence of live streaming video promotion, price discounts and online customer reviews simultaneously has a significant effect on purchasing decisions through Tiktok live streaming.

Electronic Device Control System through Voice Assistant with Rapid Application Development (RAD) Method

The purpose of this research was to assist each householder controling electronic devices when traveling in a quite distance. Therefore, apply microcontroller technology in the form of an electronic device control system via voice commands was necessity in other that it can cover a wide distance when it was connected to the internet. In this research, Voice command was controlled through a voice assistant on the user's cellphone. The way to implement it was by using several microcontroller components, including the NodeMCU ESP8266 and ESP32-CAM modules which function as indoor surveillance camera. whereas other supporting components, used FTDI as a USB to connect the ESP32-CAM as the power source, relays as automatic switches that could supply or cut off current electric to the electronic devices, and jumper cables as a link to components. Then, the system was tested both software and hardware used to find out whether the system was running well as expected. The workflow of the electronic device control system through this voice assistant began with the user giving voice commands through the voice assistant to control electronic devices both to turn on and off devices and to open CCTV cameras. The results of research showed that the voice assistant can properly accepted the voice commands given with a time span of 1 second for each command to turn on or turn off electronic devices. Likewise with the camera from the ESP32-CAM which functioned properly so that the browser can displayed indoor live stream video. That's why, the electronic device control system via voice assistant had been successfully designed and running properly using all the components mentioned above. So that users can controled electronic devices even though they were far from home by utilizing the existing internet connection now.

Future of Agro Industry with Advance Monitoring using Thingspeak

bstract: In India, an important growing sector is agriculture. The major challenges in agriculture are crop productivity, soil nutrient level, smart irrigation system, crop monitoring, etc. This paper reviews the internet of things (IoT) based smart agriculture system using Thing Speak. The main purpose of this work is to improve the efficiency of the existing. Irrigation system and to reduce the human intervention for the complete automation of the system. The proposed system consists of raspberry pi, various sensors, and a motor driver. Raspberry pi is the main controlling unit that can control the operation of various sensors and actuators. The soil moisture sensor detects the moisture level in the soil and irrigates the crop in a controlled manner. If there is any variation in moisture level then the sensor will update the observed value and store in the cloud. In a smart monitoring system, will update the observed value and store in the cloud. In a smart monitoring system, transfers it to the cloud through raspberry pi. Here Pi is used to provide live video streaming. All this sensor data is stored in a Thing Speak cloud. So that we can view it from a remote location using Thing View Free mobile android application. All this sensor data we can also view on Thing Speak.

PANDANGAN HUKUM PIDANA ISLAM DAN HUKUM POSITIF TERHADAP EKSPLOITASI LANSIA PENGEMIS ONLINE

This research aims to analyze the phenomenon that occurred during the Covid-19 pandemic which required people to work to make money without having to interact directly in the real world. This is the basis for the emergence of creative ideas for content creators to use social media to earn money. As happened recently, content creators use elderly people to become actors in a live streaming video on TikTok media. If seen from the content creator's point of view, it is very profitable, because when the video goes viral and can attract the sympathy of the audience, the audience will not hesitate. to give gifts. It's different for the elderly actor who takes extreme measures such as soaking in dirty water and mud for hours just to get sympathy and gifts. The focus of the research is the views of Islamic criminal law and positive law regarding the exploitation of elderly beggars online. This research is library research or what is called normative juridical. The data source used is secondary data. The data collection technique used is document or literature study, then the data is analyzed descriptively qualitatively. The results of the research show that in Islamic criminal law the content creator has committed slavery which ignores the health of the elderly in order to gain profit, so that he can be subject to ta'zir sanctions, namely sanctions given by Ulil Amri or the government. Meanwhile, from a positive legal perspective, perpetrators/content creators of online exploitation of elderly beggars can be sentenced to imprisonment for a minimum of 3 years, a maximum of 15 years. And a fine of at least Rp. 120,000,000.00 (one hundred and twenty million rupiah) and a maximum of Rp. 600,000,000.00 (six hundred million rupiah). Keywords: Exploitation, Elderly, Online Begging, Islamic Criminal Law, Positive Law.

Visual-haptic feedback for ROV subsea navigation control

Subsea engineering operations, including subsea inspection, installation and maintenance, heavily rely on the seamless interaction between remotely operated vehicles (ROV) and human operators. Subsea ROV control has always been a great challenge to human operators due to the dynamics of the subsea environment such as uncertainty of turbulence, affected visibility and interference with subsea ecosystems. Compared to engineering work on the ground, subsea engineering tasks are usually finished in a limited vision field with drift and localization problems. However, the traditional ROV feedback system, the live video streaming, cannot provide direct and intuitive perceptions of remote ROV workspace as well as a clear indication of the workspace uncertainties. Therefore, this research proposes a Virtual Reality augmented visual feedback system with haptic simulators to generate immersive, intuitive and effective feedback for human operators. The system can generate visual and haptic feedback as indications of flow conditions based on sensory data. A human subject experiment was performed to verify the effectiveness of this system. The result indicated that this system could significantly assist human operators in precepting the flow conditions in the ROV workspace in a more immersive and intuitive way.

The Influence of 'Ome TV': Exploring the Impact on Students' Listening Skills through Video Live Streaming

This quantitative research study investigates the influence of the video live streaming application 'Ome TV' on students' listening skills. Undergraduate students from a vocational university in Makassar, Indonesia participated in the study, which utilized an online questionnaire to collect data on participants' listening abilities and their experiences with 'Ome TV'. The study aims to investigate the influence of 'Ome TV' on students' listening skills, identify challenges faced by students in using the application for listening practice, understand students' perceptions of the application's effectiveness, and provide recommendations for optimizing the integration of video live streaming applications in language learning environments. The findings reveal that most students perceived an improvement in their listening skills through 'Ome TV'; however, difficulties such as infrequent usage, limited improvement in understanding words with similar sounds, security concerns, and network quality issues were reported. The study concludes with practical recommendations for educators, curriculum designers, and developers to enhance the use of video live streaming applications in language learning settings. These findings contribute to the understanding of the potential benefits and challenges associated with video live streaming applications for improving students' listening proficiency.

Interaction matters: Co-viewing facilitates learning from live video streaming for elementary students.

With the development of information technology, co-viewing of live video streaming (LVS) has become a popular online learning method. However, existing studies have found inconsistent results regarding the effects of co-viewing, which could be due to the impact of learner-learner interactions. The present study tested the effects of co-viewing LVS on learning in elementary students, and whether learner-learner interaction moderated students' attention allocation, learning performance (i.e., retention and transfer), learning efficiency, and metacognition. The study used a one-way between-subjects design, with 86 participants assigned randomly to one of three groups: learning alone group, merely co-viewing group, or co-viewing with interaction group. Kruskal-Wallis H tests showed that students in the co-viewing with interaction group allocated more attention to their co-viewer and less to the LVS. However, ANOVA results indicated that they had the best learning performance and metacognition, and demonstrated the highest learning efficiency. Meanwhile, those co-viewing without interaction did not show significantly positive effects compared to those learning alone. The results of informal interviews were largely consistent with the above findings. The findings of the present study suggest the benefits of co-viewing with interaction, providing practical implications for the social context of learning from LVS for elementary students in particular.

Online Versus Offline Rate in Streaming Codes for Variable-Size Messages

One pervasive challenge in providing a high quality-of-service for live communication is to recover lost packets in real-time. Streaming codes are a class of erasure codes that are designed for such strict, low-latency streaming communication settings. Motivated by applications that transmit messages whose sizes vary over time, such as live video streaming, this paper considers the setting of streaming codes under variable-size messages. In practice, streaming codes operate in an “online” setting where the sizes of the future messages are unknown. “Offline” codes, in contrast, have access to the sizes of all messages, including future ones. This paper introduces the first online rate-optimal streaming codes for communicating over a burst-only packet loss channel for two broad parameter regimes. These two online codes match the rates of optimal offline codes for the two settings despite the apparent advantage of the offline setting. This paper further establishes that online codes cannot attain the optimal rate for offline codes for all remaining parameter settings.

Micro Spy Bot

Micro robots with live audio and video streaming capabilities can help in tracking human beings during earthquakes and also perform underground surveys. This mini spy car can inspect very minute hole areas that are not accessible to humans. Hence these Micro-bots are essential to find people stuck under collapsed buildings due to earthquakes. These small micro-size robots are equipped with a camera that helps in spying or helps the army and intelligence system in collecting information and live video footage and activity on the enemy and terrorists. But designing such micro-sized SPY BOTs is very complicated. Hence the proposed design of micro-sized SPY BOTs size is not-longer than a small finger and can go easily in minute holes to collect the data. Robots have been making inroads to human life in almost all spheres. Spy bots can be immensely useful for unmanned surveillance and covert spying operations. If online streaming of the spied data can be made feasible, that would be an added advantage. In this paper, we propose an unmanned Spybot that can be controlled remotely from web-page based commands, using a WIFI network. It can also stream back the spied data that could be video or images, over the WIFI network