BOATPILOTYELLOW PAPERProject technical description

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BoatPilot ™ / Yellow paper

The BoatPilot project consists of 5 key modules.

1. VECTOR GEONAVIGATIONAL INFORMATION (GEOSPATIAL STRUCTURES) OPTIMIZATION MODULE

Problem. Since mobile devices have limited computing power and RAM, the size of the geo-navigational database must be minimized in order to function on such devices. Another limitation is the speed of accessing specific parts of the database for fast visualization on the device screen, which, in turn, requires storage with random reading capabilities.

Solution. Today, PostGIS is one of the most popular database extenders on the market. This is a module for the PostgreSQL object-relational database. Unfortunately, PostGIS cannot be used on mobile devices and users must resort to the Mapsforge binary format. However, even in binary format, the size of the output file (for example, the Mediterranean region) is greater than 10 GB, which is still too large for a mobile device. The reason is that most data suppliers (for example, OSM) are bloated and lack optimal storage structures. For example, a coastline contour can be encoded as 1,000 curves with a resolution of 1 meter, but it is much more efficient to present it as 10 curves with a resolution of 100 meters without significant loss of accuracy. Depth charts can be presented with a vertical resolution of 0.1 meters, which is also clearly excessive for the private yachting sector. Additionally, using several data suppliers means that part of the information is duplicated.

All of the above raise reasons for optimization to make the database usable on mobile devices. One of the ways we choose to solve the size problem is by using variable resolutions depending on depth. For example, having 1-meter resolution for depths up to 5 meters, and raising the resolution as depth increases. This does not affect navigational capabilities, but significantly enhances performance and reduces the amount of data stored and processed.

Our algorithm will find and eliminate such redundancy, which in turn will cut the size of the database to a fifth. Industry standard library GDAL (Geospatial Data Abstraction Library) will be used as the database library for all geo-data. GDAL is a stable high-speed library, supported by the community, as well as by large commercial and non-profit organizations such as Oracle and the Royal Canadian Geographical Society. A key feature of our algorithm is its parallelization. It allows you to use MapReduce algorithms on a computing cluster. The software algorithm is implemented via Python using ZeroMQ to distribute tasks throughout computing nodes. The common and open ESRI Shapefile is used as an output format, allowing the results to be used not only on mobile devices, but in the vast majority of GIS packages (Geographic Information System).

Further development will allow us to optimize the data storage format and load arbitrary parts of the map with the selected details.

2. HIGHLOAD CLOUD SERVER PLATFORM FOR COLLECTIVE WORK ON GEOREFERENCES WITH ARBITRARY DATA STRUCTURE AND GEODATA RANKING AND INDEXING FUNCTIONS.

Problem. In addition to coordinates, many geographical objects have a set of user characteristics. For example, the characteristics of a lighthouse must include its light stream and the shape of its base. On the other hand, in cases of marinas, contact information and the types of vessels it can accommodate must be included. Many users can add to or change these attributes, which leads us to the second problem—the asynchronous nature of such edits and additions. As many editors are used while offline, changes reach the database only after some time during synchronization. Hence, there is a need to resolve conflicts between editing and searching by an attribute value.

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BoatPilot ™ / Yellow paper

Solution. We will use PostgreSQL v9.4 as the basis of the BoatPilot module. This will provide document-oriented capabilities that are on a par with specialized NoSQL solutions. At the same time, due to the PostGIS extension, indexes will be taken into account while associating arbitrary object structures with GIS data.

Our platform will provide versioning and conflict resolution capabilities, using both a pessimistic strategy and manual data merging in the event of conflicting attribute changes.

Additionally, our platform will automatically integrate incoming edits from trusted sources, provide an interface for manual analysis and comparison of edits, and determine the degree of trust based on the history of the source's edits and social connections. At the basic level, this will be implemented using Python-based REST interfaces and AngularJS-based WEB UI. Heuristic algorithms of trusted users and workspace optimization to increase operator productivity in case of manual conflict resolution will also be improved.

3. CLOUD SERVER PLATFORM FOR REALTIME COLLECTION AND VISUALIZATION OF OBJECTIVE INDICATORS (COORDINATES, SPEEDS AND COURSES) OF VESSELS EQUIPPED WITH A GLONASS AND/OR GPS GEOLOCATION DEVICE, AS WELL AS STORAGE AND CLOUD SYNCHRONIZATION SERVER

Problem. We solve several problems simultaneously by collecting objective

indicators:

•Yacht owners and charter companies only have access to onboard navigators, but cannot analyze their route in detail, which is important for further analysis, reporting and subsequent route planning or business strategy development.

but cannot analyze their route in detail, which is important for further analysis, reporting and subsequent route planning or business strategy development.

1 Bathymetry is the study of the underwater depth of seafloors. Among specialists, this term can be used to collectively refer to all submarine topography data.

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•Solutions that are currently available to record routes cannot group information for later analysis and, as a rule, do not have the ability to automatically send data to cloud storage.

•The available depth charts are often inaccurate and do not reflect the optimal path to enter marinas or bays.

Solution. Technically, tracks are packaged in a high-efficiency streaming format based on Google Protocol Buffers and sent to the cloud using the REST interface, where they are stored for later processing. This solution will save all of the track’s necessary attributes—coordinates, speeds, course—with high temporal detail. When integrated with the onboard network, BoatPilot will add depth, fuel capacity, prevailing winds data, and any other information from the onboard sensors.

The next step will be to create bathymetry1 based on collective data and to use it to refine existing charts.

We also plan to implement a visualization and comparison interface for existing tracks based on mobile devices and a universal web interface.

for later analysis and, as a rule, do not have the ability to automatically send data to cloud storage.

path to enter marinas or bays.

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4. INNOVATIVE WIRELESS HARDWARE MODULE BOATGOD FOR IOS AND ANDROID PLATFORMS DESIGNED TO WORK WITH THE VESSEL'S ONBOARD SYSTEMS BASED ON THE NMEA STANDARD, WHICH RECEIVES INFORMATION FROM ALL THE VESSEL'S DEVICES AND, IF NECESSARY, MANAGES THEM. BOATGOD IS ALSO CAPABLE OF AGGREGATING GEOINFORMATION FROM VARIOUS SYSTEMS, LIKE THE VESSEL'S SONAR, TO COMPILE UPDATED CHARTS.

Problem. Most yachts sailing the seas today have onboard networks that combine all the vessel's sensors and control hardware components such as SIMNET, for example. This includes hardwired, as well as wireless solutions present on the market. Unfortunately, such networks are comprised of several closed and proprietary formats that differ from each other in minute details that make them incompatible with each other.

Solution. We are developing a hardware module called BoatGod, which allows a navigation program installed on a tablet computer to connect to onboard networks, thereby providing the ability to analyze information and receive/send data to the onboard network. After receiving the protocol specification, we can get data from all sensors on an Android- or iOS-based portable device for further visualization and analysis using the track synchronization module.

Additionally, BoatGod users will be able to control onboard devices such as the vessel's autopilot, engine, onboard lighting, and media system. With BoatGod, skippers will be able to monitor the status of all the vessel's systems and manage them. We also plan to give BoatGod capabilities to remotely control NMEA-compatible devices.

The end users of these solutions are not only private owners, but also large charter companies interested in remotely monitoring all onboard systems, from electronic devices to engines, of vessels currently in use by their clients.

Thus, modules will allow users to fully control the vessel, collect and analyze geo-information to refine navigational data, and quickly obtain navigational information synchronized with personal mobile devices.

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BoatPilot ™ / Yellow paper

5. AUGMENTED REALITY FUNCTION

The augmented reality (AR) function is based on collected data and provides advanced navigation and vessel control capabilities. Being a modern trend, AR proves to be quite useful in marine navigation.

The augmented reality (AR) function is based on collected data and provides advanced navigational and vessel control capabilities. AR is a trendy technology that is being used even where there is no objective need for it, but it has proven to be quite useful in marine navigation.

Navigating is never easy, but it becomes increasingly difficult in the dark, in bad weather conditions, or in unknown and dangerous waterways. Skippers must be masters at controlling vessels whose displacement can amount to dozens of tons, while simultaneously monitoring a variety of readings, as well as the vessel's position relative to navigational landmarks. Such landmarks include, but are not limited to rocks, reefs, fairway borders, port facilities, mooring lines, and other vessels.

The BoatPilot augmented reality engine superimposes all this data on a visual image. In other words, beacon data will be displayed directly above it, fairways will be projected in space, the distance to the nearest hazard will be shown in dynamics, and a system of alerts will warn the skipper of any critical conditions on the vessel.

We implemented a separate app, modest in its resource demands, specifically for Epson AR glasses. The app works in parallel with the main BoatPilot application, receiving data on the planned route, waypoints, and other key information. The Epson headset application is responsible for visualizing and superimposing all the necessary navigational information on the surface. As such, after setting the necessary objectives on the navigator, skippers can concentrate completely on yacht control, without being distracted by the navigator screen and dash. We plan to significantly expand the list of supported AR headset manufacturers in 2018.