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INSPEM Video Analysis Revolution

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The INSPEM service was introduced in 2015; it lets users find other people they encounter randomly on the subway, in parks or other locations. We assume that such services will be used by male audiences. However, as statistics show, women make up 40% of all announcements. The women have taken photos of people they love on the road from a distance, uploading those photos to our service and waiting for some acquaintances to recognize the man and share his social networking profile.
By 2016 already, we decided to change course. Our desire to reach the multibillion market and become a more technologically advanced company, which uses artificial intelligence and is able to apply video analysis based on learning neural networks for facial recognition - this has formed a new vision of the INSPEM platform.
PROBLEM
All current solutions are local and limited:
● search is limited by a particular database.
● video data received from a limited number of devices (government-owned cameras, commercial cameras in certain objects).
Search missing people
Quite a lot of time elapsed from the point someone has been lost until the beginning of their search. The search team and police are still searching for missing persons using outside flashlights and abandoned buildings. If the person does not want it at the federal or international level (which is not the case in such cases), their families have little or no chance of finding them in another city.
Often information about the movement of people can be obtained more quickly, more technological approach. There is currently no integrated database, to which one can upload a person's image to track their movements around the city or country. The police have one database, Interpol has another, the search team has another and so on. All of these factors stand the fast way of determining the location of a particular person or their movement.
Search Bystander / witness
Looking for someone, who is in a certain place at a certain time and you need to contact them? Find someone on the subway or in the nearby park / bar / car that is interesting, and you do not know how to find it?
Criminal search
Have a wallet, purse or other valuable item stolen? Find witnesses or video footage of the scene.
For the majority of citizens, access to third-party recording surveillance cameras is still not possible. Usually only becomes possible after an appeal to the police or based on a judge's decision. Very important in those cases, when the tape is there must be obtained quickly.
Every city has a continuous blind zone problem; it is a zone outside the camera of sight. This problem is even more pronounced in small towns.
SOLUTION
Main feature
● Large-scale INSPEM service allows searching anywhere in the corner of the Earth.
● The INSPEM ver.2.0 platform will use advanced video analytics based on neural network learning for the fastest and most effective facial recognition.
Our solution
Our technology is built around the main principle: can find someone without disclosing their personal information, which is most important in most of the countries
Anyone on the planet will be able to connect all IP cameras, smartphones, or recorders driving to our platforms at the software level. Connections will be established by means of DynDNS or P2P services, which are the most accessible to regular users. The camera will stay in the same place and record as usual. The only requirement is the Internet connection.
The user then logs into INSPEM, registering the camera by specifying the serial number and password. After that, the service requests the location of the camera network from the vendor's server and passes it to the nearest (in case of network) host to be processed. What we get is decentralization and minimal network load. Server vendors together with INSPEM participate in the connection establishment phase, while INSPEM tracks analytic operations and receives results.
The INSPEM platform does not record video from a user camera on its side: first, it will violate our privacy principle, secondly, it's very colossal amount of data, storage that will be expensive and unnecessary for us.
Given the large amount of data being analyzed from the video cameras around the world, we are forced to use the capacity of miners. This allows an easy passing of the scale limit, in which each local video analysis system is bound. Decentralization will also encourage effective distribution of network traffic, so it will be as short as possible.
Each user will be able to upload the image of the person searched to the INSPEM Service. What we get is huge databases of people, on one hand, and a large number of video cameras (up to 1 million potential market devices), which analyze continuous face flow in real time.
When a match is found, the platform switches both sides with valuables: a prize to the owner of the video camera for the resources provided, and images from recognizing faces with the geographic coordinates of the video camera. This is what happens in detail.
The search starts, and the possibility of a positive outcome has emerged. Users browse through them and click on the one that he thinks is the correct additional information. That is precisely the action that is considered a true positive result that harms the user, for example, the price of 0.01 $. After that, the user accepts geolocation and bids to watch the recorded footage taken with that particular episode, but it will cost the additional user 1 $. When a user selects a preview, the platform uploads a video fragment to its server without the camera owner's authorization requirement (the owner accepts or rejects the feature at registration), and saves it for 1 day. If the user decides not to pay for the full video, the INSPEM platform automatically removes it from the server after 24 hours has elapsed.
Token Information
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Token Distribution 
● 80% of token will be distributed to investors during ICO; 
● 15% tokens will be dedicated to founders and developers; 
● 5% tokens will be spent within the campaign grace framework
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● 40% - development and integration. Develop an INSPEM platform based on an existing MVP with in-machine learning (artificial intelligence) and blockchain technology. Partner system integration with INSPEM platform and "smart city" connection to access possible number of cameras worldwide. Remodeling mobile apps and web platforms. Develop our own API for interaction of each video device with our software. 
● 30% - marketing costs for participation in international exhibitions, PR, users and partners involved for rapid exponential growth; 
● 20% - principal funds for the maintenance of liquidity tokens and token exchange INP buybacks from investors; 
● 10% - operating expenses for office, legal support.
Sales during PRE-ICO and Bonus
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PRE-SALE 
[Mar. 20, 2018 - Apr 16, 2018] 
Hard stamp: 2,000 ETH 
Token Price: 1 ETH = 5 000 INP 
Bonus: 50-100%
Sales during ICO and Bonus
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ICO 
[May. 1, 2018 - May 28, 2018] 
Hard cap: 30,000 ETH 
Token price: 1 ETH = 5 000 INP 
Bonus: 0-30%
Road Map of Inspem
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INSPEM TEAM INFORMATION
  1. Mikhail Bondarenko, CEO of Founder. 
    Graduated from Federal Federal University of Russia, «Protection of a special communication system», retained a graduation thesis on «Biometric means of person identification." Having business experience since 2010. Successfully embarked on 5 projects, both in retail and on the Internet 
    Facebook: https: // www.facebook.com/bondarenko17
    LinkedIn: https://www.linkedin.com/in/mikhail-bondarenko-2b987790/
  2. Vyacheslav Jhurkin, CTO. 
    Have a technical radio education. Survailance and access control system engineers. Has 8 years experience of implementing complex IT solutions for Sberbank and other banks, government structures, hydroelectric plants. 
    LinkedIn: https://www.linkedin.com/in/vyacheslav-jhurkin-8b1a3515b/
  3. Alexdander Strakh, Smart-Contract Developer. 
    Graduated from State Engineering Bauman Moscow University. Have more than 10 years high load system develop and 3 years development of blockchain. Encoding languages: Solidity, C ++, JavaScript. 
    LinkedIn: https://www.linkedin.com/in/cromlehg/
  4. Andrey Jhukov, iOS and Android developer. 
    Technical Education. Over 10 years coding experience. Have 5 years experience of Android and iOS 
    Linked Application Development https://www.linkedin.com/in/andrey-jhukov-629a3615b/
  5. Alexander Matvienko, System Administrator. 
    Technical Education. Over 10 years of network administration and server maintenance experience. C ++ 
    LinkedIn coding skills https://www.linkedin.com/in/%D0%B0%D0%BB%D0%B5%D0%BA%D1%81%D0%B0%D0%BD%D0% B0% D0% B0% B0% D0% B0% D0% BD% D0% BA% D0% BE-807a3715b / D0% D0% B0% D1%
  6. Lidiya Tarakanova, PR Manager. 
    Graduated from university teacher, foreign language faculty. Taught English and Spanish languages. Have a 5 years marketing campaign experience. 
    LinkedIn: https://www.linkedin.com/in/%D0%BB%D0%B8%D0%B4%D0%B8%D1%8F-%D1%82%D0%B0%D1%80%D0% B0% D0% BA% D0% B0% D0% BD% D0% BE% D0% B2% D0% B0-1baa3415b /
  7. Boris Gorokhov, lawyer in China 
    Graduated from Shanghai Politics Science and Law University. Legal affairs in China and Asia market. 
    Facebook: https://www.facebook.com/bridge2china
    LinkedIn: https://www.linkedin.com/in/bridge2china/
  8. Anna Derkunskaya, Graphic Designer 
    A highly experienced graphical interface designer
  9. Vitaliy Murugov, Lawyer. Economist 
    He graduated from Agricultural University with a degree of "Lawyers", as well as the State University of Technology Kuban with a degree in experience "Economist" Lawyer since 2010. 
    Facebook: https://www.facebook.com/profile.php?id=100008736155525

Authors: YarisRiyadi1st

My Profile Bitcointalk : https://bitcointalk.org/index.php?action=profile;u=1756824;sa=summary

My ETH: 0x8B1820FB5829696cA5b595d09dF4e0F5757a97A7

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