Evalueserve

evalueserve

LOCI Information and Overview The process through which inventors create and investors fund an idea to bring it to market is fundamentally flawed. Large sums of money are wasted on inefficient processes required to bring an invention to market, largely due to convoluted legal requirements that must be adhered to in order to protect intellectual property. Loci’s goal is to streamline this process by providing a decentralized platform that enables inventors to promote their ideas and inventions to those who have the capital and the interest to back such ideas. By storing intellectual property on the blockchain, the inventor automatically acquires proof of concept so they can release ideas to the public without fear of others wrongfully attempting to claim ownership. Although there are a variety of tools on the market to search for new inventions, most are outdated, difficult to use and do not provide additional information or support required to bring a new invention to market. According to Loci, its new InnVenn visual mapping and search tool is significantly more effective than its four top competitors Evalueserves Treparel, Innogrpahy, Mapegy and Intelliixir. How Does InnVenn Work? Using InnVenn investors are able to search for new ideas, inventors on the other hand, may search and lay claim to any technologies that may infringe on their proprietary rights. In addition to providing a platform to find and fund inventions, the system is able to uncover opportunities that may have been overlooked by human eyes. By identifying areas where there is room for development, areas known as “Whitespaces”, InnVenn can revolutionize and accelerate the creation of new technologies, products and services. For example, if someone invented a handheld medical scanner in 2000 and later in 2007 the smart phone is created, InnVenn’s algorithms would be able to match the two technologies and uncover the opportunity to incorporate them. In essence, InnVenn links inventors with investors, but in a similar way to how the algorithms can uncover whitespaces for development, it also has the ability to pool together funds from like minded investors wishing to develop similar technologies. And by utilizing the blockchain to develop the system, Loci’s InnVenn platform can provide equal opportunities to access the information and contact the necessary parties required to develop innovation. Real World Applications of Loci’s InnVenn Platform What problems does InnVenn solve? Global intellectual property laws a responsible for a highly chaotic landscape in which inventions are bought and sold. Requirements to file a patent are strict, and the current laws, recently changed from the First to Invent (FTI) to the First Inventor To File (FITF), favour larger organisations with the funds to cover the high legal fees required to apply. On average patent applications can range between $10,000 to $50,000, and that’s without any guarantee the patent will be approved. The current system also lacks transparency, which means an applicant has no idea during the 12–16 month processing period, if their invention infringes on any other prior art, a discovery that can cost the inventor everything should that be found to be the case. With these regulations, inventors on a tight budget are often beaten in the approval process losing their rights to ownership in the process. Loci have built an expansive database drawing from vast array of information and resources provided directly by the inventors. Storing this information on the blockchain automatically time stamps the entry for whilst giving the inventor proof of concept right. The idea is then made accessible to others searching for related technologies using InnVenn. Leveraging the blockchain to store such information acts as an automatic filing of ‘Public Disclosure’, from which the inventor has 6 month — 12-month period (depending on the country) to file a patent, locks out others from seeking rights to the invention. The platform also enables better communication between the client and attorney and will greatly increase the application process. Technology behind InnVenn The system’s proprietary machine learning engine analyzes research trends in and identifies whitespaces, or gaps in the market, and as the platform begins to grow, so too will the number of these whitespace opportunities. InnVenn is designed to work in conjunction with current patent processes and procedures without the use of blockchain technology. As global patent processes change, the blockchain integration will become key to the development of investment pools process and IP marketplaces, and users will have many incentives to utilize the blockchain utility mechanisms. The platform will utilize LOCIcoin Tokens, tied to the Ethereum blockchain, to facilitate the creation, buying and selling of intellectual property. As a result the tokens could become the standard valuation metric of all IP. To support the development of the platform Loci is creating an online marketplace similar to Ebay where users can sell or purchase IPs for the development of new products. An app, dubbed the DApp, is also being developed to display data in an easy to read format, and allow users to place bids for any IPs listed within the InnVenn system. Search results are displayed in an easy-to-read Venn diagram that clearly displays the different branches related to the IP in question and how these related fields overlap one another. The multilayered diagram allows for a wide range of information to be displayed. By providing information to users in such a way, it becomes possible to physically visualise the connection between two ideas, without having to analyse long lists and strings of data. Valuable Information Loci Coin (LOCI) Coin Name : — 100,000,000 LOCI Total Supply : — Circulating Supply : — 1 LOCICOIN = 0.44 USD Pre Ico Price : — 1 LOCI = 0.75 USD Ico Price : — $7,376,751 OF $19,000,000 (39%) Tokens/Money Raised Through ICO : Who Benefits From Loci’s InnVenn Platform? Loci’s new platform provides the opportunity to quickly and efficiently search for IP whilst protecting the parties involved from infringements on copyright laws until the registration is complete. In doing so, the InnVenn platform offers benefits to all those involved bringing an invention to the market. The primary client base includes IP attorneys, enterprise IP managers, business strategists, investors, inventors, entrepreneurs, patent researchers, and patent offices, however the opensource and decentrailsed architecture of the platform means that anyone with a good idea can benefit form using the InnVenn system. Providing a streamline, more efficient method of developing inventions, InnVenn serves to avoid expensive attorney fess, assist with early research, provide real-time verification on the validity of an idea, visualise gaps in the market, and assist with communication between all parties involved. The platform has already shown much promise. The USPTO, the official United States Patent and Trademark office, has stated that it views the platform as a public data base of patents, products, and ideas; a statement that legitimizes the system significantly as a location for public disclosure. Staff / Team Info Name : John Wise Title : CEO Bio : — John brings a very diverse background to the Loci team. For more than 15 years he worked as a mechanic, crew chief, data engineer, and team manager for some of the top teams in American racing. LinkedIn : — https://www.linkedin.com/in/john-wise-14939858/ Name : Brian Hwang Title : Director of Operations Bio : — Brian has a diverse experience and expertise in the areas of strategic partnerships, business development, and operations to the team. He is an alumnus of University of Illinois at Urbana-Champaign with dual B.S. degrees in Finance and Accountancy. He has worked in a wide range of large companies and industries including Johnson & Johnson, GE Capital, and Ernst & Young. LinkedIn : — https://www.linkedin.com/in/brian-hwang-191a053/ Name : Eric Ross Title : Director of Technology Bio : — Eric was a software developer for more than 10 years and worked for a wide variety of companies and utilizing various technologies as a consultant. He has a B.S. in applied physics/computers from Grove City College. LinkedIn : — https://www.linkedin.com/in/ericsross/ Name : Harjit Singh Title : Lead Developer Name : Nivas Narayanasamy Title : Developer Name : Hudson Burgess Title : Developer Name : Abdelal Ali Title : Developer Name : Dan Emmons Title : Blockchain/Solidity Developer Name : Sean Brizendine Title : Blockchain Specialist Name : Lauren Arevalo Title : Content Marketing Manager Name : Zaimah Khan Title : Digital Marketing Manager Name : Jesse Lucas Title : Marketing & PR Name : Kelly Weaver Title : Marketing & PR Name : Jesse Johnson Title : Asia Team Lead Name : Klajdi Ciraku Title : Community Manager Name : Jasmeen Saini Title : QA Analyst Name : Claire Naumann Title : Executive Assistant Name : Charlie Kiser Title : Advisor Bio : — Blockchain and Cryptocurrency Expert and Entrepreneur. Name : Carl Grant III Title : Advisor Bio : — Carl Grant III is EVP, Business Development for Cooley and he is known as a super-connector in the entrepreneurial ecosystem and a trusted advisor to CEOs. Name : Bryan Feinberg Title : Advisor Bio : — With a background in Venture Capital, Capital Raising & Structuring, Brian currently serves on the ICO certification board to help improve ICC standards for ICO issuers that apply for Financial Commission’s ICO certification service. Name : Brett Berlin Title : Advisor Bio : — As a founding member of the ISOC-DC chapter of the Internet Society, Brett is focused on Internet policy, as a member of IEEE-USA Policy Advisory Committees, and of NIST standards working groups (cloud and big data). Name : David Drake Title : Advisor Bio : — David is the Chairman of LDJ Capital, a family office; Victoria Partners, LDJ Real Estate Group; Drake Hospitality Group; and, The Soho Loft Media Group. LDJ Capital’s extended network of funds and hedge funds manages 1.5 trillion USD in assets. David previously represented the US Commerce Department at the EU and he spoke at the UK Parliament. LinkedIn : — https://www.linkedin.com/in/ldjcapital/ Name : Tony Sousa Title : Advisor Bio : — CEO of Sierra Wealth Development, with experience in business structure, private placement, capital acquisition and hi-tech financing. He has a background in entrepreneurial technology and is a leader in sales and marketing. Name : Michael Brunner Title : Advisor Bio : — Dr Michael J Brunner received his B.S. from the University of Wisconsin and his Doctor of Pharmacy from the University of Iowa. He is leading efforts to transform the pharmaceutical and healthcare industry using the principles and innovations of blockchain technology. Dr. Brunner is currently the CEO and Founder of BlockMedx. Name : Chris Berlin Title : Advisor Name : William Schrader Title : Advisor Name : Matt McKibbin Title : Advisor Name : Richard Titus Title : Advisor Social Media and Contact Facebook URL : — https://www.facebook.com/Loci.InnVenn/ Likes : 1,897 likes and 2,013 followers How Many Posts / Updates In The Last 7 Days : 1 post Twitter URL : — https://twitter.com/loci_io Followers :6229 followers How Many Tweets / Retweets In The Last 7 Days : 2 posts Telegram URL : — https://t.me/Loci_InnVenn Users : 3 030 members Company Address : Sterling, VA, USA

LOCI Intellectual Property Discovery and Mining: Get Paid For Your Ideas On The Blockchain

In my last post, we looked at metrics via the Amazon CloudWatch SDK. Health monitoring is a super important topic that is crucial to keeping your live streaming applications performant. Another crucial element is viewer analytics. In this post, we'll look at a few ways to provide insight into stream viewers. monitoring Amazon Interactive Video Service (Amazon IVS) live stream health Much of this post will look similar to my last post. That's because viewer data is also stored in CloudWatch and can be retrieved via the SDK. There is one additional method, as we'll see below, to get a count of the current viewers of a live stream which is a handy way to get a count that can be displayed on your front end. While this post focuses on live stream channel viewers, you can also retrieve metrics about your Amazon IVS chat rooms like and messages . We won't cover that in this post, but you can check out the to learn more. Note: ConcurrentChatConnections Delivered docs Retrieving Concurrent Views via the CloudWatch Console If you're just looking for a glance at viewer data without retrieving the raw data, you can view your via the CloudWatch console. First, select , then choose . ConcurrentViews All metrics IVS Next, select . By channel Then select the checkbox in the row that contains for any of your Amazon IVS channels. ConcurrentViews Another way to find concurrent views for a stream session is via the Amazon IVS console. Select your channel, then choose a from the channel details page. Stream id The details for a stream session will contain several charts, one of which contains the for the session. Concurrent views Retrieving Concurrent Views via the CloudWatch SDK To integrate this data into your own application, you can retrieve the data via the CloudWatch SDK. Similarly to health metrics, you'll need a the channel's , a , and an to retrieve . ARN StartTime EndTime ConcurrentViews Instead of randomly choosing the start and end times, it probably makes sense to dynamically obtain these times by choosing the start and end times from a live stream session. You can retrieve a list of stream sessions via the Amazon IVS SDK (as we saw in the ). previous post You'll always need an , even for streams that are currently live. For live streams, you can always use the current time as the when using the SDK to retrieve metrics. Reminder: EndTime EndTime To retrieve this data via the AWS SDK for JavaScript (v3), you will need to install the package and create an instance of the client ( ). After the client instance is created, set a few variables for the required inputs. @aws-sdk/client-cloudwatch new CloudWatchClient() const startTime = new Date('2023-02-10T14:00:00.000Z');
const endTime = new Date('2023-02-10T14:30:00.000Z');
const arn = process.env.DEMO_CHANNEL_ARN; Next, create an input object. The input object will contain the , , and an array of . The queries array will contain a single object that specifies the ( ), the ( ), and the to filter by (channel name, in this case). StartTime EndTime MetricDataQueries MetricName ConcurrentViews Namespace AWS/IVS Dimensions const getMetricDataInput = {
  StartTime: startTime,
  EndTime: endTime,
  MetricDataQueries: [{
    Id: "concurrentviews",
    MetricStat: {
      Metric: {
        MetricName: "ConcurrentViews",
        Namespace: "AWS/IVS",
        Dimensions: [{ Name: "Channel", Value: arn.split("/")[1] }]
      },
      Period: 5,
      Stat: "Average",
    }
  }],
  MaxDatapoints: 100
}; Now send the request and log the result. const getMetricDataRequest = new GetMetricDataCommand(getMetricDataInput);
let metrics = await cloudWatchClient.send(getMetricDataRequest);
console.log(metrics); Which produces output that looks like the following (extraneous SDK metadata removed for brevity): {
  "MetricDataResults": [
    {
      "Id": "concurrentviews",
      "Label": "ConcurrentViews",
      "Timestamps": [
        "2023-02-10T14:29:00.000Z",
        "2023-02-10T14:28:00.000Z",
        "2023-02-10T14:27:00.000Z",
        "2023-02-10T14:26:00.000Z",
        "2023-02-10T14:22:00.000Z"
      ],
      "Values": [
        3,
        3,
        3,
        3,
        10
      ],
      "StatusCode": "PartialData"
    }
  ]
} You can filter, sort, and output this data to produce a format useful for generating charts. const viewMetrics = metrics
  .MetricDataResults
  .find((metric) => metric.Id === 'concurrentviews');

const viewValues = viewMetrics.Values.reverse();

const viewData = [];

viewMetrics
  .Timestamps
  .reverse()
  .forEach((t, i) => {
    viewData.push({
      timestamp: t,
      concurrentviews: viewValues[i],
    })
  });

console.log(JSON.stringify(viewData)); Which produces an array of objects. [
  {
    "timestamp": "2023-02-10T14:22:00.000Z",
    "concurrentviews": "10.00"
  },
  {
    "timestamp": "2023-02-10T14:26:00.000Z",
    "concurrentviews": "3.00"
  },
  ...
] You can use this data with our favorite charting library (or a generic online chart generator like I did). Generating Chart Images with the CloudWatch SDK In the last post, we looked at generating the image directly via the CloudWatch SDK. This approach also applies to your view metrics. const startTime = new Date('2023-02-10T14:00:00.000Z');
const endTime = new Date('2023-02-10T14:25:00.000Z');
const arn = process.env.DEMO_CHANNEL_ARN;

const cloudWatchClient = new CloudWatchClient();
const getMetricWidgetImageInput = {
  MetricWidget: JSON.stringify({
    metrics: [
      [
        "AWS/IVS",
        "ConcurrentViews",
        "Channel",
        arn.split("/")[1]
      ]
    ],
    start: startTime,
    end: endTime,
    period: 5,
    stat: "Average"
  })
};
const getMetricWidgetImageRequest = new GetMetricWidgetImageCommand(getMetricWidgetImageInput);
const metricImage = await cloudWatchClient.send(getMetricWidgetImageRequest); Which returns an object with the key that contains an array buffer ( ) containing the chart image. MetricWidgetImage Uint8Array {
  "MetricWidgetImage": {
    "0": 137,
    "1": 80,
    "2": 78,
    ...
  }
} To convert this array buffer to a base64 string: const buffer = Buffer.from(metricImage.MetricWidgetImage);
console.log(buffer.toString('base64')); Which gives us: iVBORw0KGgoAAAANSUhEUgAAAlgAAAGQCAIAAAD9V4nPAAAACXBIWXMA... That can be converted to an image that looks like so: Retrieving Current Live View Sessions for a Channel As mentioned above, you can easily get a count of the current view sessions for the active live stream on a channel via the Amazon IVS client module in the AWS SDK. For this, use the method. GetStream import { GetStreamCommand, IvsClient } from "@aws-sdk/client-ivs";

const client = new IvsClient();

const getStreamCommandInput = {
  channelArn: process.env.DEMO_CHANNEL_ARN,
};
const getStreamRequest = new GetStreamCommand(getStreamCommandInput);
const getStreamResponse = await client.send(getStreamRequest);
console.log(getStreamResponse); Which produces output like the following. {
  "stream": {
    "channelArn": "arn:aws:ivs:us-east-1:[redacted]:channel/[redacted]",
    "health": "HEALTHY",
    "playbackUrl": "https://[redacted].us-east-1.playback.live-video.net/api/video/v1/us-east-1.[redacted].channel.x4aGUUxIp5Vw.m3u8",
    "startTime": "2023-02-10T15:46:36.000Z",
    "state": "LIVE",
    "streamId": "st-[redacted]",
    "viewerCount": 5
  }
} Note the property which is a live count of view sessions for the current live stream. viewerCount Summary In this post, we learned how to retrieve view data for our Amazon IVS live streams via the CloudWatch and Amazon IVS SDKs. To learn more, check out the . documentation Crown

How to Monitor Live Stream Viewer Analytics with Amazon IVS

Cómo monitorear Live Stream Viewer Analytics con Amazon IVS

Comment surveiller les analyses de la visionneuse de flux en direct avec Amazon IVS

Amazon IVS के साथ लाइव स्ट्रीम व्यूअर एनालिटिक्स की निगरानी कैसे करें

Amazon IVS を使用して Live Stream Viewer 分析をモニタリングする方法

Como monitorar a análise do visualizador de transmissão ao vivo com o Amazon IVS

Cách theo dõi Phân tích người xem phát trực tiếp với Amazon IVS

如何使用 Amazon IVS 监控实时流查看器分析

Stories, News & Mentions about EVALUESERVE

Evalueserve’s Stories on HackerNoon