DeepWater Treasure Recovery

DeepWater Treasure Recovery

Created using Figma
Created using Figma
Stiamo lanciando DeepWater, un nuovo progetto, che impiega l'intelligenza artificiale per il riconoscimento di modelli subacquei. Abbiamo in programma di raccogliere informazioni sui naufragi e le risorse minerarie sottomarine nel Mar dei Caraibi e lungo le rotte commerciali storiche nell'Oceano Atlantico e nell'Oceano Pacifico.
Rischio: alto
Sale
28 feb 2018
14 mar 2018
100% completato
Fondi raccolti - nessun dato
past
Dettagli del token
telescrivente
DWT
Valute accettate
ETH, BTC
Dettagli della Compagnia
Paese registrato
Ecuador
dettagli aggiuntivi
categorie
piattaforma, Servizi per gli affari, Produzione, Turismo, Big Data, Intelligenza artificiale

Di DeepWater Treasure Recovery

Investors have long been interested in two main aspects of deep-water exploration. First, shipwrecks and sunken treasures. In the Atlantic Ocean alone, according to some estimates, over 100,000 ships were lost, with cargo worth trillions of dollars. Second, deep-sea mining. According to the reports of the British Geological Society, ocean resources of some precious metals, including cobalt, nickel, and gold, are thousand times larger than the existing continental reserves. Oceans and seas have an unmatched investment potential. However, current archaic fragmented methods of deep-water exploration pose serious obstacles to business development in these areas. In the vast high seas, the key to success has always been quality data on where to search. Exploratory expeditions often rely on incomplete historical records, approximate calculations, theories, intuition, and luck. Needless to say, many return on shore empty handed.

And now imagine that it is possible to eliminate uncertainty and errors. It is possible to know for sure the exact coordinates of a shipwreck with valuable cargo or the location of a rich mineral deposit. Anyone, from amateur treasure hunters to large corporations interested in deep water mining would be able to buy access to data about millions of square kilometers of seabed. Tens of thousands of deep-water explorers would get a chance to buy information about promising coordinates with discovered shipwrecks, mineral resources, and anomalies.

DeepWater team will collect, analyze, and present these data on the DeepWater Market.©, platform. For three years, our team has been developing DeepWater Syst.©, a unique large-scale information and measurement system to collect and interpret data patterns from the seabed. We built on existing underwater scanning technology but enriched it with Artificial Intelligence (AI) and adapted it to create specialized gliders to collect data about sunken objects, natural formations, and other features of the seabed. Gliders conduct underwater scanning and supply information to the DeepWater Neural Network, which learns to recognize underwater patterns. Each new expedition of the fleet of gliders would add more datasets to enhance the system’s Deep Learning process and increase the rate of recognition up to 98-99%.

We plan to begin a systematic scanning of the seabed along the historical trade routes between the New and the Old World in the Caribbean Sea, in the Atlantic and Pacific Oceans. Based on the information collected by DeepWater gliders, we will form a centralized database of underwater shipwrecks and mineral resources. This information will be available for sale on an online auction platform DeepWater Market.© to any interested registered user. At this stage, we will use blockchain technology to securely store the data and ensure its integrity. Only the buyer will have access to the coordinates of the sold lot. Blockchain would guarantee that neither DeepWater team, nor anyone else can alter the data or re-sell it after the purchase is made. To increase profits, DeepWater team would reserve 20% of all the promising lots for recovery by its own means or jointly with partners. Every year we plan to recover 1-2 ships with valuable cargo.

Our highly skilled team of robotics experts, systems engineers and developers has already created a unique new generation technology, which sets us three years ahead of any possible competitors. To truly benefit from the potential of Deepwater Syst. ©, we need to build the largest fleet of autonomous gliders in the world. To start a glider assembly line, we are crowdfunding resources by means of token sale on the Ethereum platform. Deepwater Syst. © is a disruptive innovation on the market, which will profoundly change the business of treasure recovery and deep-sea mining. The world is on the verge of a major technological breakthrough in deep-water exploration, which will bring along incrediblediscoveries and multi-billion profits already in the next few years.

Caratteristiche

Il mercato DeepWater & nbsp; userà & nbsp; la tecnologia blockchain, che garantisce l'integrità e l'archiviazione sicura dei dati relativi alla scoperta risorse di acque profonde:
◈ & nbsp; & nbsp; & nbsp; Dati del sonar
◈ & nbsp; & nbsp; & nbsp; Dati del magnetometro
◈ & nbsp; & nbsp; & nbsp; Foto ad alta risoluzione e copertura video del oggetto o della superficie del fondo marino per l'estrazione in acque profonde
◈ & nbsp; & nbsp; & nbsp; Profondità dell'oggetto / posizione del deposito, informazioni sulla corrente (velocità), temperatura dell'acqua
◈ & nbsp; & nbsp; & nbsp; Dimensione / superficie dell'oggetto
◈ & nbsp; & nbsp; & nbsp; Risultati di laboratorio (contenuto di metallo nel terreno campioni)

Informazioni tecniche

Il token DeepWater (DWT) è un token compatibile ERC20 all'interno della blockchain della piattaforma Ethereum.

% name% Roadmap

  • 2015

  • Glider Prototype Development
  • Q1 2016

  • - Testing the Concept
    - Glider Prototype Launch in Ecuador Closed Waters
  • Q2 2016

  • - Initial data collection
    - Neural Network Development
  • Q3 2016

  • Glider Prototype Launch in Ecuador Inshore Waters
  • Leggi di più
  • Q4 2016

  • Initial Neural Network training based on the acquired data
  • Q1 2017

  • Neural Network testing in a Virtual Underwater Simulator (UWSims)
  • Q2-Q4 2017

  • - Glider prototype launch in offshore
    - Additional data accumulation for Deep Learning
    - System debugging
    - Logistics network optimisation
    - "glider-to-glider" and "glider-to-ship" communication system debugging
  • Q1 2018

  • "DWT" Token pre-sale/sale
  • Q1-Q2 2018

  • Distribution of Tokens "DWT"
  • Q1-Q2 2018

  • Distribution of Tokens "DWT"
  • Q2 2018

  • Listing "DWT" on Cryptocurrency Exchanges
  • Q2-Q4 2018

  • - Filing paperwork to purchase land and to start the construction of an assembly line
    - Hiring assembly line personnel
    - Setting up an international logistics network and signing contracts with the suppliers of parts
    - Launch of the glider assembly line
    - Start of the development of the Deepwater Market platform
    - Hiring marketing and PR personnel
  • Q1-Q4 2019

  • - Launch of the first exploratory expedition by the fleet of gliders
    - DeepWater Market.© platform launch and blockchain integration
    - Start of a large-scale advertising campaign for DeepWater Market.©
  • Q4 2019

  • - Loyalty program execution: start of DWT buy-back
  • 2020

  • - Increasing the number of lots on DeepWater Market.©, start of the recovery of some discovered shipwrecks

Attività

Attività:
140
MEDIUM
Merito:
11
LOW
Messaggi:
66
VERY LOW
Visualizzazioni:
1 787
LOW
utenti:
27
LOW

DeepWater Treasure Recovery Squadra

verificata 0%

Attenzione. C'è il rischio che i membri non verificati non siano effettivamente membri del team

Alej­andro Gavri­lyu...
CEO, Founder
non verificato
Manuel Merino
Software Engineer
non verificato
Fernando Moreira
Software Engineer
non verificato
Eduardo Perez
System Engineer
non verificato
Julio Cruz
Software Engineer
non verificato
Alfredo Casero
System Engineer
non verificato
Pedro Vela
Software Engineer
non verificato
Rodrigo Intriago
Systems Engineer
non verificato
Carlos Alvarado
Systems Engineer
non verificato
Jose Saltos
Marine Surveyor
non verificato
3.33
risky+
5.0 3
ICO Profilo Visione Attività Potenziale Prodotto Squadra
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