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• How to Stream RTP (IP camera) Into React App setup

  10 novembre 2024, par sharon2469

  I am trying to transfer a live broadcast from an IP camera or any other broadcast coming from an RTP/RTSP source to my REACT application. BUT MUST BE LIVE

  


  My setup at the moment is :

  


  IP Camera -> (RTP) -> FFmpeg -> (udp) -> Server(nodeJs) -> (WebRTC) -> React app

  


  In the current situation, There is almost no delay, but there are some things here that I can't avoid and I can't understand why, and here is my question :

  


  1) First, is the SETUP even correct and this is the only way to Stream RTP video in Web app ?

  


  2) Is it possible to avoid re-encode the stream , RTP transmission necessarily comes in H.264, hence I don't really need to execute the following command :

  


      return spawn('ffmpeg', [
    '-re',                              // Read input at its native frame rate Important for live-streaming
    '-probesize', '32',                 // Set probing size to 32 bytes (32 is minimum)
    '-analyzeduration', '1000000',      // An input duration of 1 second
    '-c:v', 'h264',                     // Video codec of input video
    '-i', 'rtp://238.0.0.2:48888',      // Input stream URL
    '-map', '0:v?',                     // Select video from input stream
    '-c:v', 'libx264',                  // Video codec of output stream
    '-preset', 'ultrafast',             // Faster encoding for lower latency
    '-tune', 'zerolatency',             // Optimize for zero latency
    // '-s', '768x480',                    // Adjust the resolution (experiment with values)
    '-f', 'rtp', `rtp://127.0.0.1:${udpPort}` // Output stream URL
]);


  


  As you can se in this command I re-encode to libx264, But if I set FFMPEG a parameter '-c:v' :'copy' instead of '-c:v', 'libx264' then FFMPEG throw an error says : that it doesn't know how to encode h264 and only knows what is libx264-> Basically, I want to stop the re-encode because there is really no need for it, because the stream is already encoded to H264. Are there certain recommendations that can be made ?

  


  3) I thought about giving up the FFMPEG completely, but the RTP packets arrive at a size of 1200+ BYTES when WEBRTC is limited to up to 1280 BYTE. Is there a way to manage these sabotages without damaging the video and is it to enter this world ? I guess there is the whole story with the JITTER BUFFER here

  


  This is my server side code (THIS IS JUST A TEST CODE)

  


  import {
    MediaStreamTrack,
    randomPort,
    RTCPeerConnection,
    RTCRtpCodecParameters,
    RtpPacket,
} from 'werift'
import {Server} from "ws";
import {createSocket} from "dgram";
import {spawn} from "child_process";
import LoggerFactory from "./logger/loggerFactory";

//

const log = LoggerFactory.getLogger('ServerMedia')

// Websocket server -> WebRTC
const serverPort = 8888
const server = new Server({port: serverPort});
log.info(`Server Media start om port: ${serverPort}`);

// UDP server -> ffmpeg
const udpPort = 48888
const udp = createSocket("udp4");
// udp.bind(udpPort, () => {
//     udp.addMembership("238.0.0.2");
// })
udp.bind(udpPort)
log.info(`UDP port: ${udpPort}`)


const createFFmpegProcess = () => {
    log.info(`Start ffmpeg process`)
    return spawn('ffmpeg', [
        '-re',                              // Read input at its native frame rate Important for live-streaming
        '-probesize', '32',                 // Set probing size to 32 bytes (32 is minimum)
        '-analyzeduration', '1000000',      // An input duration of 1 second
        '-c:v', 'h264',                     // Video codec of input video
        '-i', 'rtp://238.0.0.2:48888',      // Input stream URL
        '-map', '0:v?',                     // Select video from input stream
        '-c:v', 'libx264',                  // Video codec of output stream
        '-preset', 'ultrafast',             // Faster encoding for lower latency
        '-tune', 'zerolatency',             // Optimize for zero latency
        // '-s', '768x480',                    // Adjust the resolution (experiment with values)
        '-f', 'rtp', `rtp://127.0.0.1:${udpPort}` // Output stream URL
    ]);

}

let ffmpegProcess = createFFmpegProcess();


const attachFFmpegListeners = () => {
    // Capture standard output and print it
    ffmpegProcess.stdout.on('data', (data) => {
        log.info(`FFMPEG process stdout: ${data}`);
    });

    // Capture standard error and print it
    ffmpegProcess.stderr.on('data', (data) => {
        console.error(`ffmpeg stderr: ${data}`);
    });

    // Listen for the exit event
    ffmpegProcess.on('exit', (code, signal) => {
        if (code !== null) {
            log.info(`ffmpeg process exited with code ${code}`);
        } else if (signal !== null) {
            log.info(`ffmpeg process killed with signal ${signal}`);
        }
    });
};


attachFFmpegListeners();


server.on("connection", async (socket) => {
    const payloadType = 96; // It is a numerical value that is assigned to each codec in the SDP offer/answer exchange -> for H264
    // Create a peer connection with the codec parameters set in advance.
    const pc = new RTCPeerConnection({
        codecs: {
            audio: [],
            video: [
                new RTCRtpCodecParameters({
                    mimeType: "video/H264",
                    clockRate: 90000, // 90000 is the default value for H264
                    payloadType: payloadType,
                }),
            ],
        },
    });

    const track = new MediaStreamTrack({kind: "video"});


    udp.on("message", (data) => {
        console.log(data)
        const rtp = RtpPacket.deSerialize(data);
        rtp.header.payloadType = payloadType;
        track.writeRtp(rtp);
    });

    udp.on("error", (err) => {
        console.log(err)

    });

    udp.on("close", () => {
        console.log("close")
    });

    pc.addTransceiver(track, {direction: "sendonly"});

    await pc.setLocalDescription(await pc.createOffer());
    const sdp = JSON.stringify(pc.localDescription);
    socket.send(sdp);

    socket.on("message", (data: any) => {
        if (data.toString() === 'resetFFMPEG') {
            ffmpegProcess.kill('SIGINT');
            log.info(`FFMPEG process killed`)
            setTimeout(() => {
                ffmpegProcess = createFFmpegProcess();
                attachFFmpegListeners();
            }, 5000)
        } else {
            pc.setRemoteDescription(JSON.parse(data));
        }
    });
});


  


  And this fronted :

  


  &#xA;&#xA;&#xA;    &#xA;    &#xA;    <code class="echappe-js">&lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://unpkg.com/react@16/umd/react.development.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://unpkg.com/react-dom@16/umd/react-dom.development.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script&amp;#xA;            crossorigin&amp;#xA;            src=&quot;https://cdnjs.cloudflare.com/ajax/libs/babel-core/5.8.34/browser.min.js&quot;&amp;#xA;    &gt;&lt;/script&gt;&#xA;    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/babel-regenerator-runtime@6.5.0/runtime.min.js&quot;&gt;&lt;/script&gt;&#xA;&#xA;&#xA;
  &#xA;    
  
  &#xA;
  
  &#xA;&lt;script type=&quot;text/babel&quot;&gt;&amp;#xA;    let rtc;&amp;#xA;&amp;#xA;    const App = () =&gt; {&amp;#xA;        const [log, setLog] = React.useState([]);&amp;#xA;        const videoRef = React.useRef();&amp;#xA;        const socket = new WebSocket(&quot;ws://localhost:8888&quot;);&amp;#xA;        const [peer, setPeer] = React.useState(null); // Add state to keep track of the peer connection&amp;#xA;&amp;#xA;        React.useEffect(() =&gt; {&amp;#xA;            (async () =&gt; {&amp;#xA;                await new Promise((r) =&gt; (socket.onopen = r));&amp;#xA;                console.log(&quot;open websocket&quot;);&amp;#xA;&amp;#xA;                const handleOffer = async (offer) =&gt; {&amp;#xA;                    console.log(&quot;new offer&quot;, offer.sdp);&amp;#xA;&amp;#xA;                    const updatedPeer = new RTCPeerConnection({&amp;#xA;                        iceServers: [],&amp;#xA;                        sdpSemantics: &quot;unified-plan&quot;,&amp;#xA;                    });&amp;#xA;&amp;#xA;                    updatedPeer.onicecandidate = ({ candidate }) =&gt; {&amp;#xA;                        if (!candidate) {&amp;#xA;                            const sdp = JSON.stringify(updatedPeer.localDescription);&amp;#xA;                            console.log(sdp);&amp;#xA;                            socket.send(sdp);&amp;#xA;                        }&amp;#xA;                    };&amp;#xA;&amp;#xA;                    updatedPeer.oniceconnectionstatechange = () =&gt; {&amp;#xA;                        console.log(&amp;#xA;                            &quot;oniceconnectionstatechange&quot;,&amp;#xA;                            updatedPeer.iceConnectionState&amp;#xA;                        );&amp;#xA;                    };&amp;#xA;&amp;#xA;                    updatedPeer.ontrack = (e) =&gt; {&amp;#xA;                        console.log(&quot;ontrack&quot;, e);&amp;#xA;                        videoRef.current.srcObject = e.streams[0];&amp;#xA;                    };&amp;#xA;&amp;#xA;                    await updatedPeer.setRemoteDescription(offer);&amp;#xA;                    const answer = await updatedPeer.createAnswer();&amp;#xA;                    await updatedPeer.setLocalDescription(answer);&amp;#xA;&amp;#xA;                    setPeer(updatedPeer);&amp;#xA;                };&amp;#xA;&amp;#xA;                socket.onmessage = (ev) =&gt; {&amp;#xA;                    const data = JSON.parse(ev.data);&amp;#xA;                    if (data.type === &quot;offer&quot;) {&amp;#xA;                        handleOffer(data);&amp;#xA;                    } else if (data.type === &quot;resetFFMPEG&quot;) {&amp;#xA;                        // Handle the resetFFMPEG message&amp;#xA;                        console.log(&quot;FFmpeg reset requested&quot;);&amp;#xA;                    }&amp;#xA;                };&amp;#xA;            })();&amp;#xA;        }, []); // Added socket as a dependency to the useEffect hook&amp;#xA;&amp;#xA;        const sendRequestToResetFFmpeg = () =&gt; {&amp;#xA;            socket.send(&quot;resetFFMPEG&quot;);&amp;#xA;        };&amp;#xA;&amp;#xA;        return (&amp;#xA;            &lt;div&gt;&amp;#xA;                Video: &amp;#xA;                &lt;video ref={videoRef} autoPlay muted /&gt;&amp;#xA;                &lt;button onClick={() =&gt; sendRequestToResetFFmpeg()}&gt;Reset FFMPEG&lt;/button&gt;&amp;#xA;            &lt;/div&gt;&amp;#xA;        );&amp;#xA;    };&amp;#xA;&amp;#xA;    ReactDOM.render(&lt;App /&gt;, document.getElementById(&quot;app1&quot;));&amp;#xA;&lt;/script&gt;&#xA;&#xA;&#xA;
  

  


• Four Trends Shaping the Future of Analytics in Banking

  27 novembre 2024, par Daniel Crough — Banking and Financial Services

  While retail banking revenues have been growing in recent years, trends like rising financial crimes and capital required for generative AI and ML tech pose significant risks and increase operating costs across the financial industry, according to McKinsey’s State of Retail Banking report.

   

  Today’s financial institutions are focused on harnessing AI and advanced analytics to make their data work for them. To be up to the task, analytics solutions must allow banks to give consumers the convenient, personalised experiences they want while respecting their privacy.

   

  In this article, we’ll explore some of the big trends shaping the future of analytics in banking and finance. We’ll also look at how banks use data and technology to cut costs and personalise customer experiences.
  
  So, let’s get into it.

  

  This doesn’t just represent a security risk, it also impacts the usability for both customers and employees. Does any of the following sound familiar ?

  • Only specific senior employees know how to navigate the software to generate custom reports or use its more advanced features.
  • Customer complaints about your site’s usability or online banking experience are routine.
  • Onboarding employees takes much longer than necessary because of convoluted systems.
  • Teams and departments experience ‘data siloing,’ meaning that not everyone can access the data they need.

  These are warning signs that IT systems are ready for a review. Anyone thinking, “If it’s not broken, why fix it ?” should consider that legacy systems can also present data security risks. As more countries introduce regulations to protect customer privacy, staying ahead of the curve is increasingly important to avoid penalties and litigation.

  And regulations aren’t the only trends impacting the future of financial institutions’ IT and analytics.

  4 trends shaping the future of analytics in banking

  New regulations and new technology have changed the landscape of analytics in banking.

  New privacy regulations impact banks globally

  The first major international example was the advent of GDPR, which went into effect in the EU in 2018. But a lot has happened since. New privacy regulations and restrictions around AI continue to roll out.

  • The European Artificial Intelligence Act (EU AI Act), which was held up as the world’s first comprehensive legislation on AI, took effect on 31 July 2024.
  • In Europe’s federated data initiative, Gaia-X’s planned cloud infrastructure will provide for more secure, transparent, and trustworthy data storage and processing.
  • The revised Payment Services Directive (PSD2) makes payments more secure and strengthens protections for European businesses and consumers, aiming to create a more integrated and efficient payments market.

  But even businesses that don’t have customers in Europe aren’t safe. Consumer privacy is a hot-button issue globally.

  For example, the California Consumer Privacy Act (CCPA), which took effect in January, impacts the financial services industry more than any other. Case in point, 34% of CCPA-related cases filed in 2022 were related to the financial sector.

  California’s privacy regulations were the first in the US, but other states are following closely behind. On 1 July 2024, new privacy laws went into effect in Florida, Oregon, and Texas, giving people more control over their data.

  

  One typical issue for companies in the banking industry is that their privacy measures regarding user data collected from their website are much less lax than those in their online banking system.

  It’s better to proactively invest in a privacy-centric analytics platform before you get tangled up in a lawsuit and have to pay a fine (and are forced to change your system anyway). 

  And regulatory compliance isn’t the only bonus of an ethical analytics solution. The right alternative can unlock key customer insights that can help you improve the user experience.

  The demand for personalised banking services

  At the same time, consumers are expecting a more and more streamlined personal experience from financial institutions. 86% of bank employees say personalisation is a clear priority for the company. But 63% described resources as limited or only available after demonstrating clear business cases.

  McKinsey’s The data and analytics edge in corporate and commercial banking points out how advanced analytics are empowering frontline bank employees to give customers more personalised experiences at every stage :

  • Pre-meeting/meeting prep : Using advanced analytics to assess customer potential, recommend products, and identify prospects who are most likely to convert
  • Meetings/negotiation : Applying advanced models to support price negotiations, what-if scenarios and price multiple products simultaneously
  • Post-meeting/tracking : Using advanced models to identify behaviours that lead to high performance and improve forecast accuracy and sales execution

  Today’s banks must deliver the personalisation that drives customer satisfaction and engagement to outperform their competitors.

  The rise of AI and its role in banking

  With AI and machine learning technologies becoming more powerful and accessible, financial institutions around the world are already reaping the rewards.

  McKinsey estimates that AI in banking could add $200 to 340 billion annually across the global banking sector through productivity gains.

  • Credit card fraud prevention : Algorithms analyse usage to flag and block fraudulent transactions.
  • More accurate forecasting : AI-based tools can analyse a broader spectrum of data points and forecast more accurately.
  • Better risk assessment and modelling : More advanced analytics and predictive models help avoid extending credit to high-risk customers.
  • Predictive analytics : Help spot clients most likely to churn 
  • Gen-AI assistants : Instantly analyse customer profiles and apply predictive models to suggest the next best actions.

  Considering these market trends, let’s discuss how you can move your bank into the future.

  Using analytics to minimise risk and establish a competitive edge 

  With the right approach, you can leverage analytics and AI to help future-proof your bank against changing customer expectations, increased fraud, and new regulations.

  Use machine learning to prevent fraud

  Every year, more consumers are victims of credit and debit card fraud. Debit card skimming cases nearly doubled in the US in 2023. The last thing you want as a bank is to put your customer in a situation where a criminal has spent their money.

  This not only leads to a horrible customer experience but also creates a lot of internal work and additional costs.Thankfully, machine learning can help identify suspicious activity and stop transactions before they go through. For example, Mastercard’s fraud prevention model has improved fraud detection rates by 20–300%.

  

  Implementing a solution like this (or partnering with credit card companies who use it) may be a way to reduce risk and improve customer trust.

  Foresee and avoid future issues with AI-powered risk management

  Regardless of what type of financial products organisations offer, AI can be an enormous tool. Here are just a few ways in which it can mitigate financial risk in the future :

  • Predictive analytics can evaluate risk exposure and allow for more informed decisions about whether to approve commercial loan applications.
  • With better credit risk modelling, banks can avoid extending personal loans to customers most likely to default.
  • Investment banks (or individual traders or financial analysts) can use AI- and ML-based systems to monitor market and trading activity more effectively.

  Those are just a few examples that barely scratch the surface. Many other AI-based applications and analytics use cases exist across all industries and market segments.

  Protect customer privacy while still getting detailed analytics

  New regulations and increasing consumer privacy concerns don’t mean banks and financial institutions should forego website analytics altogether. Its insights into performance and customer behaviour are simply too valuable. And without customer interaction data, you’ll only know something’s wrong if someone complains.

  Fortunately, it doesn’t have to be one or the other. The right financial analytics solution can give you the data and insights needed without compromising privacy while complying with regulations like GDPR and CCPA.

  That way, you can track usage patterns and improve site performance and content quality based on accurate data — without compromising privacy. Reliable, precise analytics are crucial for any bank that’s serious about user experience.

  Use A/B testing and other tools to improve digital customer experiences

  Personalised digital experiences can be key differentiators in banking and finance when done well. But there’s stiff competition. In 2023, 40% of bank customers rated their bank’s online and mobile experience as excellent. 

  Improving digital experiences for users while respecting their privacy means going above and beyond a basic web analytics tool like Google Analytics. Invest in a platform with features like A/B tests and user session analysis for deeper insights into user behaviour.

  

  Behavioural analytics are crucial to understanding customer interactions. By identifying points of friction and drop-off points, you can make digital experiences smoother and more engaging.

  Matomo offers all this and is a great GDPR-compliant alternative to Google Analytics for banks and financial institutions. 

  Of course, this can be challenging. This is why taking an ethical and privacy-centric approach to analytics can be a key competitive edge for banks. Prioritising data security and privacy will attract other like-minded, ethically conscious consumers and boost customer loyalty.

  Get privacy-friendly web analytics suitable for banking & finance with Matomo

  Improving digital experiences for today’s customers requires a solid web analytics platform that prioritises data privacy and accurate analytics. And choosing the wrong one could even mean ending up in legal trouble or scrambling to reconstruct your entire analytics setup.

  Matomo provides privacy-friendly analytics with 100% data accuracy (no sampling), advanced privacy controls and the ability to run A/B tests and user session analysis within the same platform (limiting risk and minimising costs). 

  It’s easy to get started with Matomo. Users can access clear, easy-to-understand metrics and plenty of pre-made reports that deliver valuable insights from day one. Form usage reports can help banks and fintechs identify potential issues with broken links or technical glitches and reveal clues on improving UX in the short term.

  Over one million websites, including some of the world’s top banks and financial institutions, use Matomo for their analytics.

  Start your 21-day free trial to see why, or book a demo with one of our analytics experts.

• Data Privacy Day 2020

  27 janvier 2020, par Matthieu Aubry — Privacy
  It’s January 28th which means it’s Data Privacy Day !

  Today is an important day for the Matomo team as we reflect on our mission and our goals for 2020. This year I wanted to send a video message to all Matomo users, community members and customers. 

  Check it out (full transcript below)

  

  A video message from Matomo founder, Matthieu Aubry

  Privacy-friendly alternatives

  • NoMoreGoogle :
    a comprehensive list giving you options for other privacy-friendly alternatives.
  • Switching.Software :
    Ethical alternatives to popular sites and apps.
  • Web browser :
    Firefox
    Brave
    Vivaldi
  • Search engine :
    DuckDuckGo
    Qwant
  • File sharing :
    Nextcloud
  • Email provider :
    ProtonMail
    Mailfence
    Tutanota

  Video transcript

  Hey everyone,

  Matthieu here, Founder of Matomo.

  Today is one of the most significant days of the year for the Matomo team – it’s Data Privacy Day. And so I wanted to quickly reflect on our mission and the significance of this day. 

  In today’s busy online world where data is king, this day is an important reminder of being vigilant in protecting our personal information online.

  Matomo began 12 years ago as an open-source alternative to Google Analytics – the goal was, and still is to give full control of data back to users. 

  In 2020, we are determined to see through this commitment. We will keep building a powerful and ethical web analytics platform that focuses on privacy protection, data ownership, and provides value to all Matomo users and customers.

  And what’s fantastic is to see the rise of other quality software companies offering privacy-friendly alternatives for web browsers, search engines, file sharing, email providers, all with a similar mission. And with these products now widely available, we encourage you to take back control of all your online activities and begin this new decade with a resolution to stay safe online.

  I’ll provide you with some links below the video to check out these privacy-friendly alternatives. If you have a website and want to gain valuable insights on the visitors while owning your data, join us ! 

  Matomo Analytics On-Premise is and always will be free to download and install on your own servers and on your own terms.

  Also feel free to join our active community or spread the word to your friends and network about the importance of data privacy.

  Thank you all and wishing you a great 2020 !

  For more information on how Matomo protects the privacy of your users, visit : https://matomo.org/privacy/

  Do you have privacy concerns ?

  What better day than today to speak up ! What privacy concerns have you experienced ?

  Contact Support