Koleksi ICO: INSPEM

"INSPEM" - VIDEO ANALYTICS REVOLUTION FOR PEOPLE SEARCH

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The INSPEM service was introduced in 2015; it allows users to find other people that they have randomly encountered on the subway, in the parks or any other locations. We assumed that such kind of service would predominantly be used by the male audience. However, as the statistical data shows, females made 40% of all announcements. Ladies have been simply taking pictures of the guys they liked on the streets from the afar, uploading those pictures to our service and waiting for some acquaintance to recognize that guy and share his social network profile.

This is exactly what the first version of the product was a few years ago. At the time of foundation of the service we wanted to become some sort of an analogue of «Wait for me» TV show, but as an online service. For your information: «Wait for me» is a Russian TV show that helped to find more than 200 000 of people since it first aired in 1999. A new request to find people from all corners of the Earth is received every 10 minutes. More than 3 million of lost people are in the show’s database. There are only two countries, in which «Wait for me» does not search for people yet, and those are Antigua and Barbuda and Cape Verde.

PROBLEM

Missing people search

Quite a lot of time passes from the point a person has gone missing until the start of the search for them. Search squads and police still search for missing people using flashlights in the outdoors and abandoned buildings. If that person is not wanted on a federal or international level (which does not happen in such cases), their relatives have little to no chances to find them in another city. It’s often that the information on persons movement could be obtained through quicker, more technological approach. There is currently no unified database, to which one could have uploaded a person’s picture to track their movements around the city or the country. The police has one database, the Interpol has another, the search squads has yet another and so on. All these factors stand in the way of quick determination of the specific person’s location or their movements.

Bystander/witness search

Looking for a person, who was in a specific place at specific time and you need to contact them? Found someone on a subway or in a park/bar/nearby car attractive, and you do not know how to find him or her?

Criminals search

Got your wallet, bag or other valuable item stolen? Find witnesses or video footage from the crime scene. For the majority of citizens the access to the third-party surveillance cameras footage is still impossible. It usually becomes possible only after an appeal to the police or by the judge’s decision. It is critical in those cases, when the footage has to be obtained swiftly. Each city has a continuing «blind» zone problem; those are the zones outside the cameras sight. This problem is even more pronounced in the small towns.

SOLUTION

Our solution Our technology is built around the main principle: being able to find a person without revealing their personal information, which is of utmost importance in most of the countries. Any person on the planet would be able to connect any IP-camera, smartphone or a driving recorder to our platform on a software level. The connection would be established by the means DynDNS or P2P services, which are the most accessible for the regular user. The camera would remain at the same place and record footage as usual. The only requirement is the Internet connection.

Then the user logs into INSPEM, registers his camera by specifying its serial number and password. After that, the service requests the network location of the camera from the vendor’s server and passes it to the nearest (in terms of the network) host for processing. What we get is the decentralization and the minimal network load. Vendor’s servers together with INSPEM participate in the connection establishment stage, while INSPEM tracks the analytics operations and receive results. The INSPEM platform does not record videos from the user cameras on its side: firstly, that would violate our confidentiality principle, secondly, that is a colossal amount of data, the storage of which would be costly and unnecessary for us.

Schematic representation of the interaction process:

For government structures

We are quite open for collaboration with the government services, which conduct people searches, but are limited with their resources or meet with one or more of the following obstacles: lack of video cameras in certain areas, dead zones, poor video quality, etc. We aim to become a direct contributor to the establishment of safe cities. Here is the example: mass events. In order to provide safety the government organs connect to the platform, specify the event’s area and upload their criminals’ pictures database. This becomes a priority task for INSPEM. Additional miners are being connected and the enhanced analysis is being carried out.

To save people’s lives

The rescue services and the fellow citizens who help a sick bystander could use our technology. Here's an example: a person on the street with a heart failure requires urgent assistance. Bystanders show certain gestures to the nearest surveillance camera, in a few minutes a drone that carries a diffibrilator/medkit/oxygen mask/etc appears. As a first prototype solution we consider collaboration with Ambulance Drone by TuDelft.

For users

Our technology allows to solve a lot of everyday tasks, when you do not know the first and last names of the person, who was in a specific location at a specific time. An example of such tasks: a person got their bag stolen or lost their documents and knows the approximate position of that event. He submits an announcement to the system with a specified geolocation, and all the bystanders who were in that spot at that time can help them. Perhaps, they saw that incident or captured something relevant on their car’s driving recorder.

Who pays for this?

The most concerned person in our structure is the user, who searches for specific people or witnesses/bystanders from a certain scene. They require information on a person, or a footage from the scene. These people are ready to pay for the valuable information. They already pay us within the framework of current INSPEM service with not fully realized functionality.

Why blockchain?

On a worldwide scale, processing of large video streams require huge capacities and resources. Our platform is compatible with the «smart» cameras that already perform the primary video processing and provide ready face images, which would significantly reduce the network load. Nevertheless, not everybody have such cameras. That is why we will employ miners' capacities as the most effective and rational mean for video analytics based on neural networks.

Important

It is important to note, that the user of the service will not be able to receive access to any video camera, both to an online translation and the archived footages. It is done, of course, in safety concerns. The video footage may be received only in two cases:

if the video analytics automatically detect the required face;
if the camera owner by their own decide to transmit a specific footage clip, which, for example, contains the car crash moment.

The first and second cases both require user to pay for the footage. These rules rule out the possible abuse intents, as well as the simply curious people, who thought they could get the information about their neighbor's movement for free.

MONETIZATION

The key moment is that the user who searches for a person or a footage from the scene pays.

It is reasonable and understandable. It is very normal to pay a price of a few INP tokens or hypothetical dollars to receive a footage of their missing relative, of a thief, who has stolen a bag and were caught in sight of the car’s driving recorder. Or a footage of car, which has hit your automobile on a parking lot and disappeared without a trace.

Only the INSPEM service earns revenue

Any user may submit one people search announcement (both acquainted and stranger) with the picture, description and geolocation of a desired person. For an additional fee, the user may highlight their announcement or place it at the top of the list. There are also several tariffs, which increase the number of available announcements, offer different notification means, etc. The user pays for the abovementioned options directly to our service.

Any user earns revenue, and the INSPEM takes a small fee

There is also an earning opportunity for every user. There are several options.

To place a video camera on a building’s balcony or a private home’s face, specify its GPS-coordinates. If the user already have video surveillance installed, it is enough to specify the coordinates and receive notifications from those who wish to receive the footage of a specific period (usually, a few minutes and less). The users sets his own price for the provided footage.
The user may draw a route where they have driven their car on the map by placing the key points. Anyone, who needs the footage from their driving recorder, may purchase it. There is another option available: the person opens the map with already marked spots, where the footage have been requested for specific times. If the user was in the required place at the required time, they may sell the footage taken by them.
The user, who has captured the pictures at the show, bar or crowded crossroad on his smartphone’s camera is able to sell those pictures, if they would interest anyone. Of course, the video data is more valuable, but in some cases even a single picture may be of a certain value.
The user may or may not have photo or video material; however, there is still an opportunity to earn revenue on INSPEM for them. If another user is searching for a specific person (even without their full name), published their picture and the built-in face recognition instruments fail to identify them, it is possible to identify them manually for an additional fee.

Complex solutions for government structures and large IT giants

There is one of the trusted solutions. Hikivision unifies the camera and network videotape recorder with the NVIDIA Jetson, cloud servers based on NVIDIA Tesla P4 accelerators and the powerful computational capabilities of the DGX-1 AI supercomputer for the learning. This complex is capable of performing very serious tasks. This solution is unavailable for regular users. Yet, we can lay the very first link of this chain on the users’ shoulders. INSPEM is able to receive video data from a million of user cameras all around the world, which the government structures are unable to do.

MARKET ANALYSIS

Today video is the world’s largest data generator, received from the hundreds of millions of cameras, installed in the government facilities, public transport, commercial building and on the roads. By 2020, the overall number of the cameras around the planet should reach 1 billion, according to the NVIDIA prognosis.

The worldwide video surveillance market volume has approached the number of $30 billion. The trend is that the hardware market share becomes progressively smaller. The larger share is being overtaken by the services and software, which allow to process the video data received from the cameras.

MARKET PLAYERS

In 2017 the platform started collaboration with Alibaba and Huawei, which unify over 50 of the world’s leading companies. As was mentioned above, the overall number of the video cameras by 2020 would reach more than 1 billion, and they would solve numerous issues through NVIDIA Metropolis. Metropolis makes the cities safer and smarter through the artificial intelligence video streams algorithms in applications for public safety provisions. Moreover, we would be directly involved in this process.

In addition, down below the key video analytics market members are presented. They do not offer the product that we can offer; therefore, we cannot view them as our direct contestants. We already started negotiating partnership with some of the displayed companies.

Herta is a European company that developed its own face recognition algorithm, which employs deep machine learning based on NVIDIA processors. It has several subdivisions which all have something to do with face recognition for different segments: judicial analysis, marketing goals, access control, public places safety, gambling, etc

The DeepVision was found in 2014 and has created a video analytics product, which employs the AI. DeepVision works with two main directions. Firstly, the visual face analysis. The face detection and recognition of images and videos. The demographical analysis is being carried out. The personalized content is generated for the safety systems. Secondly, the brand recognition. The system detects and recognizes brands, logos and products for further analysis.

A company from China, where it is the leading AI developer. It specializes on innovational computer systems, including the deep machine learning technologies. It has a wide variety of products, from the smartphone authentication to the video analytics for industrial systems and urban structures.

American company. Its main product is CityEyes, which is a PaaS cloud platform with a Big Data open architecture. Looking forward, this system would be integrated into more than 30 video analytics mechanisms. The IronYun company widely uses the machine learning and artificial intelligence technologies, developed in the leading universities of the USA.

Greek company, the Computer Vision software developer, which uses the image processing and machine learning methods, created for any CPU, GPU or DSP / ASP or their combination platform with use of heterogeneous programming methods. The software may be used on mobile devices, surveillance cameras, drones, in the car construction, etc.

Cloud computing (SaaS) based video analytics software, based on the Deep Learning technology, which turns hundreds and even thousands of surveillance cameras into smart video devices, which promote safety and timely incident reaction within the whole town. Has two main products: SavVi and InnoVi.

The Xjera Labs Pte Ltd was found in Singapore in 2013, it specializes on Image and Video Analytics (VA) solutions development, based on the AI. Collaborates with NVidia and IMDA Singapore in terms of GPU usage for application of Deep Learning methods for the increased accuracy.

Russian company, its LUNA PLATFORM product is a system for data management for face verification and identification. The platform is very flexible in terms of creating face recognition scenarios of any complexity. The LUNA PLATFORM is based on the LUNA SDK – a face recognition engine, developed by the VisionLabs.

TOKENOMICA

The INP token essence INP – is an Ethereum based token, which supports the ERC-20 standard. The INP token is a utility-token, since it is only appropriate for usage of the INSPEM platform’s internal features. The token holders do not received dividends and do not participate in company managements. Therefor INP is not a securitytoken and is not affected by the financial regulators.

Token name: INP

Platform: Ethereum

Token standard: ERC 20

Base price of a single token: 1 ETH = 5000 INP

Minimal transaction: 0.1 ETH

Emission and the IPN token distribution

The IPN tokens would be released once during the ICO. The further emission of tokens is not intended. The Ethereum smart-contact was created for the fund raising during Pre-Sale and ICO, it’s published on the open GitHub repository: https://github.com/CROMLEHG/INSPEM

80% of tokens would be distributed to investors during the ICO;
15% of tokens would be dedicated to founders and developers;
5% of tokens would be spent within the bounty campaign framework.

40% - development and integration. Developing the INSPEM platform based on the already existing MVP with deep machine learning (artificial intelligence) and blockchain technology. Integration of partner systems with the INSPEM platform and the «smart cities» connection in order to access the maximal possible number of cameras around the world. Renovation of the mobile applications and web-platform. Developing of our own API for interaction of any video devices with our software.
30% - marketing expenses for participation in the international exhibitions, PR, users and partners engaging for swift exponential growth;
20% - primary fund for token maintenance of token exchange liquidity and INP buy-back from the investors;
10% - operating expenses for the office, legal support.

Realization of Pre-Sale

Start: 20th of March 2018 at 13:00:00 GMT

End: 16th of April 2018 or when the HardCap is reached

Hard Cap: 2 000 ETH INP base token cost: 1 ETH = 5000 INP

Minimal transaction: 0.1 ETH

INP token purchase bonuses during Pre-Sale for early investors

Realization of ICO

Start: 1st of May 2018 at 13:00:00 GMT

End: 28th of May 2018 or when the HardCap is reached

Hard Cap: 30 000 ETH INP base token cost: 1 ETH = 5000 INP

Minimal transaction: 0.1 ETH

INP token purchase bonuses during ICO for early investors

ROADMAP

The first concept of the project was introduced in 2014. Firstly, we held a consultation concerning the biometric data (photo and video) processing without personal data reveal issues, involving, among others, the Federal Supervision Agency for Information Technologies and Communications.

TIM

Mikhail Bondarenko

CEO Founder

Graduated from the Russian South Federal University, «Protected communication systems» specialty, defended the graduation thesis on «Biometric means of person identification». Has business experience since 2010. Sucessfully started 5 projects, both in retail and the Internet.

Vyacheslav Jhurkin

CTO

Has a radio technical education. Survailance and access control systems engineer. Has an 8-year experience of implementation of complex IT-solutions for Sberbank and other banks, government structures, hydroelectric power plants.

Alexdander Strakh

Smart-Contract Developer

Graduated from the Bauman Moscow State Technical University. Has over 10 years of high-load systems developing and 3 years of blockchain developing. Coding languages: Solidity, C++, JavaScript.

Andrey Jhukov

iOS and Android developer

Technical education. More that 10 years of coding experience. Has a 5-year experience of Android and iOS application developing.

Alexander Matvienko

System Administrator

Technical edcucation. More than a 10-year network administration and server maintenance experience. C++ coding skills.

Lidiya Tarakanova

PR Manager

Graduated from the teacher's university, foreign languges faculty. Taught English and Spanish languages. Has a 5-year marketing campaign experience.

Boris Gorokhov

lawyer in China

Graduated from the Shanghai University of Political Science and Law. Legal affairs in China and Asian markets.

Anna Derkunskaya

Graphic Designer

Highly experienced graphic interface designer.

Vitaliy Murugov

Lawyer. Economist

He graduated from the Kuban state Agrarian University with a degree in" Lawyer", as well as the Kuban state Technological University with a degree in" Economist " Lawyer experience since 2010.

That's the explanation about INSPEM which Digital Science can convey., hopefully can be useful for friends of cryptocurrency lovers. Thanks and look forward to information about other crypto worlds.