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National digital transport platform

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Description

Improved transport management, such as taxi and flights and passenger control, advanced person identification and simplified visa processing adds to the digital transportation system. Benefits of which are: tourism and counties safety development

Problem

Human factors have a significant impact on the transportation system. Destructive behavior, smuggling of prohibited substances, and terrorism pose daily threats to the safety of passengers and transportation personnel. Issues with passenger flow control and communication systems prevent providing a sufficiently high level of quality for trips and travels. Obtaining a visa is another problem faced by the transportation system, which can take a lot of time and require significant expenses from the applicant. It limits the flow of tourists and business people, which can have a negative impact on the country’s economy and tourism development.

Solution

Improving control over passenger flow. The system allows to control the number of passengers and their departure and destination points, which contributes to more efficient use of transport and improves passenger safety. Simplifying the process of passenger identification. Thanks to the identification system, passengers can quickly and easily go through the security procedure, which speeds up the boarding process and reduces queues. Simplifying the visa processing. This allows tourists and businessmen to obtain visas faster and easier, which contributes to the development of tourism and business in the country.

Alternative nitrogen fertilizer for soil

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Description

Soil health can be improved by nitrogen fixing bacteria. Nitrogen-fixing bacteria helps to convert atmospheric nitrogen into a form that plants can use.

 

Problem

More than 33% of soil is depleted due to constant malnutrition and erosion. The main feature of soil is its ability to provide nutrients for crops and greenery, supplying the food chain. The most consumed nutrients are nitrogen, phosphorus, and potassium. While these nutrients can be replenished by nature, it can be inefficient and can take a long time. To combat this, humanity has started using fertilizers, which can restore soil resources more effectively than nature. However, this method can have negative effects on the soil if misused, requiring multiple uses and several steps. No more than 90% of fertilizer nutrients are consumed by crops, with the rest being eroded away. Such methods are not very effective due to the harsh usage or long time required for resource restoration.

 

Solution

One potential method to improve soil health and nutrients, and reduce the environmental impact of agriculture is the use of nitrogen-fixing bacteria. These bacteria help to convert atmospheric nitrogen into a form that plants can use, thus reducing the need for conventional fertilizers. Additionally, the use of nitrogen-fixing bacteria can help to improve soil health and reduce erosion. While the use of these bacteria may not completely replace conventional fertilizers, they can be used in combination with them to reduce the overall amount of synthetic fertilizers needed. Furthermore, the use of nitrogen-fixing bacteria can also have positive impacts on the surrounding ecosystem by reducing runoff and limiting the release of harmful chemicals into the environment.

UAV identification and localization

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Description

TDOA (Time Difference Of Arrival), also known as multilateration, is a well-established technique for identifying and localizing unmanned aerial vehicles (UAVs). By using three or more receivers, TDOA algorithms can calculate the location of the UAV based on the differences in arrival times of the signal at each receiver. This technology allows for quick and accurate identification and localization of UAVs, which is important for security and safety purposes.

 

Problem

Many people are wary and suspicious of drones. Drones are increasingly being used for a wide range of purposes, from photography to surveying and heat loss surveys. However, the flight of a drone over private property can raise legal and practical issues that need to be addressed. Businesses can become concerned about their privacy and security and there are general concerns about trespass, and safety. Drones, if not used responsibly, can be dangerous. Traditional method of the UAV detection system utilizes radar technologies. Those systems detect objects by emitting radio waves in short pulses. If this signal hits an object, it bounces back to the radar antenna. The radar then amplifies the reflected signal to find out how big the object is, and how fast it’s moving. Even if a traditional radar system can detect very small objects, most only tell you that an object is there, not what it is. Drone detection radars that can’t automatically classify whether an object is a bird or a drone could cause confusion and waste time.

 

Solution

A cutting-edge drone detection suite uses TDOA (Time Difference of Arrival) to primarily detect when a UAV is operating in controlled airspace. TDOA works by calculating the time difference between the signal’s arrival at various radio receivers. After the signal from the drone is received at the various receivers, it is triangulated using the speed of electromagnetic waves in the air to determine the emitter’s location. This process utilizes hardware and software designed for detecting drones and gives the location information as output to the security team through an integrated or standalone gateway. The hardware used is a very high-frequency range-sensitive receiver with a very stable and precise clock, such as GPSDO (GPS Disciplined Oscillator). This precise clock source is used to synchronize the detectors and time stamp when they receive a specific signal for accurate detection and localization of UAVs, which is essential for security and safety purposes.

Smart Snail Farm

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Description

Smart Snail Farm is an innovative project that utilizes advanced technologies, including IoT, smart sensors, and machine learning, to revolutionize the snail farming industry. The project enables farmers to monitor and control all processes on the snail farm conveniently from their smartphones and computers.

 

Problem

Snail farming, or heliciculture, plays a significant role in the agricultural sector, providing both food and economic opportunities. However, traditional snail farming methods often face challenges that hinder productivity and profitability. Manual labor-intensive operations and decision-making based on limited experience are common practices. Additionally, snail diseases and other factors contribute to substantial economic losses. To unlock the full potential of snail farming, there is a need to address these challenges effectively.

 

Solution

The Smart Snails Farm project presents a groundbreaking solution for the snail farming industry. By embracing digitalization and incorporating IoT elements, this project aims to optimize snail cultivation practices. Through the integration of smart sensors continuous monitoring of snail habitats and conditions is established. The system utilizes machine learning algorithms to analyze data, allowing for the early detection and prevention of diseases. Automated decision-making processes further streamline snail farm management. The AI-based system provides accurate recommendations to farm employees, enhancing efficiency and productivity. Smart Snails Farm introduces a modern approach to snail farming, improving economic performance and setting new standards in the industry.

Smart Bee Farm

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Description 

Smart bee farm is a software and hardware complex with machine learning elements created to improve the efficiency of bee cultivation using IoT: smart sensors, video and audio sensors. The software is adapted for farmers and allows to control all processes at bee farm from a smartphone and computer.

 

Problem

Beekeeping is an important branch of agriculture, which also has a significant impact on related branches, since bees are the main pollinators of crops and flowers – up to 90% of global pollination. However, the potential of the industry is not fully realized – modern apiaries are still guided by the traditional model of beekeeping, many operations involve the use of manual labor, and decision-making is largely based on the personal experience of beekeepers. The economic losses of the apiary are largely due to bee diseases, which, despite the measures taken, remain significant. One of the main challenges is colony collapse disorder, due to which the average mortality rate in the world in recent years has been more than 20%.

 

Solution 

The Smart bee farm project is a revolution in beekeeping. Digitalization of the apiary is an opportunity to reduce losses and risks associated with the human factor, establish continuous monitoring of the condition of hives and bees, prevent bee diseases and the destruction of bee colonies. The IoT system, which includes audio, video, and other sensors, learns to analyze the situation in hives, predicting disease foci in advance. The software automates decision-making. AI-based system provides highly accurate recommendations for apiary employees, which improves the efficiency and productivity of the bee farm. This project is an opportunity to modernize the industry, change the modern understanding of beekeeping and significantly improve the economic performance of the apiary.

Chlorella production

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Description

Chlorella production is based on photosynthesis of microalgae. Relatively simple organization, high reproduction rate, and the possibility of cultivation under fully controlled conditions have made chlorella a promising direction for use in various fields.

 

Problem

Mineral fertilizers are the main fertilizers used in plant breeding. Excessive use of mineral fertilizers leads to soil depletion, decreased crop quality, accumulation of harmful substances in the soil, and leaching of additives into water sources. Some mineral fertilizers may also contain toxic substances that can negatively impact human and animal health. Therefore, it is necessary to develop and apply more efficient and safe methods of fertilization in crop production.

 

Solution

Chlorella production is based on photosynthesis of microalgae to produce high-quality proteins, fatty acids, vitamins and minerals. One of the main advantages of such production is its environmental friendliness and ensuring sustainable development. To date, the production of chlorella microalgae is characterized by productivity, ease of maintenance and economic efficiency. The main end product of production is chlorella suspension, which can be used in crop production, animal husbandry and water management.

Predictive maintenance platform

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Description

A system that allows managing and monitoring the technical condition of equipment at facilities that are crucial for the functioning of society and the economy.

 

Problem

As companies grow, it becomes increasingly difficult to control familiar processes, which in turn consume more and more resources, both in terms of labor and finances. Current methods of diagnostics cannot accurately localize malfunction.

 

Solution

Thanks to our proprietary sensors, it is possible to monitor parameters that are not accessible for control in default equipment, such as vibration, acoustic patterns, etc. Deep analysis of physical patterns is carried out using proprietary sensors, which unambiguously indicate a specific problem. Neural networks handle a huge amount of data and recognize sound anomalies in the acoustic image. The data is processed and decisions are made based on real data from specific equipment, allowing defects to be identified. The operator sees a notification about the detected anomaly, its cause, and based on this data, makes a decision about further actions.

Digital medical platform

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Description

The system that AI analyzes medical data, aimed to assist medical staff in decision-making. It provides remote consultations with specialists and automatic analyzation of images with AI to detect any health abnormalities.

Problem

The issue of modern medicine today is very relevant. Among the main problems, accessibility to quality medical care in remote areas and small towns is highlighted. The need for long trips and additional expenses significantly complicates the lives of sick people. The insufficient amount of quality diagnostic equipment in each hospital hinders accurate diagnoses and the prescription of appropriate treatment. The lack of sufficient doctors and staff is also a problem, with a heavy workload on existing specialists and the periodic need for doctor rotation, which does not always allow for quality treatment for all patients. The lack of data exchange and consultations with specialists makes it difficult to prescribe quality treatment and leads to inefficient use of doctors and hospital resources. Therefore, it is important to pay attention to these issues and work on their solution to improve medical care around the world.

Solution

The system collects and analyzes data from various diagnostic equipment, including information from medical images that pass through artificial intelligence modules. Thanks to this, the system can provide additional assistance to medical personnel in decision-making. For example, thanks to remote consultations of qualified specialists, which is especially important in regions where there is a shortage of qualified medical personnel. In addition, the system automatically analyzes images using artificial intelligence technologies, which allows detecting even the smallest deviations in the patient’s health and providing more accurate diagnosis. As a result, the system provides higher quality medical services and increases patients’ trust in the medical industry as a whole.

Agriculture Management Platform

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Description

Crop fields and types are identified from time-series of satellite data using machine learning based crop identification algorithms built from ground data and expert experiences.

Problem

Seed map is an essential tool for farmers that provides not only proper distribution of planting areas but also optimal use of resources. It allows planning of crops in a smart way, taking into account soil features, climate conditions, and other factors that can increase productivity and quality of products. Additionally, seed map can be helpful for analyzing crop results and planning future crop rotations. Therefore, creating a seed map is an important step in ensuring sustainable agriculture development and increasing production efficiency.

Solution

Time-series of satellite multispectral images are particularly useful for identifying crops. Seasonality features for each targeted crop are derived from local ground data and expert knowledge, and machine learning algorithms are used to establish the seasonality patterns. The patterns are then applied to time-series NDVI to identify crop types for each field. Finally, fields and their boundaries are detected through the seasonal composition of satellite images. With the help of algorithms, it is now possible to easily identify different types of crops in a field, allowing for more accurate analysis and predictions. This technology also allows for the identification of seasonality patterns, which is a crucial factor in predicting crop yields.

Digital educational platform

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Description

Comprehensive education informatization system, with tools for learning and communication, as well as analytical and reporting tools for students, teachers, parents, and government authorities.

Problem

The lack of a transparent system of quality control in education, financial inaccessibility of online learning resources, and primitive student-teacher communication do not allow children to fully realize their potential. It is absolutely outrageous that school websites do not even post homework, so students have to write tragic letters to their classmates, who also didn’t record anything. The economic costs associated with the widespread use of paper reporting in schools in Uzbekistan alone amount to 2.32 billion som per year. 

The COVID-19 pandemic has permanently changed traditional business processes. The demand for digital solutions in all sectors of the economy has increased, and is likely to continue to grow in the near future. Education is one of the key sectors of any country’s economy, which will continue to have a significant impact on the economy as a whole. 

Solution

Digital learning system is one of the innovative tools created to improve the educational process. Digital learning provides transparent and effective interaction between participants in the educational process, which contributes to the improvement of the level of education and academic performance of the learner. An additional advantage is the presence of information about the material learned, strengths and weaknesses in the studied material, which allows for deeper and more conscious decisions on how to improve the quality of education for all participants. The system helps establish a simple and accessible format of relationships between the teacher and the learner. 

Additionally, transitioning to online learning will free up finances from the budget allocated for paper-based bureaucracy.

Automated Analysis in Inspection and Screening Complexes

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Description

Using X-ray energy source system will provide images of the scanned vehicle. Images are processed by AI thus lifting operators’ workload and minimizing human error and ignorance factor. AI is capable of detecting abnormalities in vehicle scan and declaring found object’s class. 

Problem

Millions of cars and containers pass through checkpoints every year. Criminals use them to transport dangerous goods and substances that are restricted from being transported. To combat this, inspection and screening complexes (ISCs) are used, which use radioscopic images to analyze the vehicle and container. However, the images are processed by a specialist operator, which leads to human errors. The annual growth in supply chains, increased workload on operators processing up to 900,000 images per year, thus leading to increased risk of errors, corruption, false and sometimes deliberately inaccurate declaration of goods are problems with the current method of cargo analysis.

Solution

In addition to inspection and screening complex scanning technology for vehicles and cargo containers, AI recognition technology is used. By processing images, the neural network is capable of detecting patches in the scanned object’s structure, as well as prohibited and restricted objects of classified commodity groups. Automated analysis allows for faster processing of ICS images, better detection control, increased ICS throughput, lack of corruption and increased cargo transport safety while reducing the load on checkpoint operators. It allows for an increase in customs payments due to automatic detection of unreliable or false declaration of goods by 5-15%, and more efficient personnel management.

Infrastructure for monitoring greenhouse gasses

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Description

Monitoring the concentration of greenhouse gasses using spectral satellite imagery and exhaust sensors. The introduction of restrictive measures in the form of carbon credits and means of generating their own credits, with the help of green spaces, called carbon farms

Problem

Many greenhouse gasses occur naturally in the atmosphere, but human activity heavily contributes to their accumulation. As a result, the greenhouse effect in the atmosphere is boosted and it alters our planet’s climate, leading to shifts in snow and rainfall patterns, a rise in average temperatures and more extreme climate events such as heatwaves and floods. 

In light of this, more than 110 countries have committed to achieving zero emissions by 2050.

Solution

Spectral imaging is able to detect the presence and concentration of greenhouse gasses in the atmosphere. Based on this method, many research satellites in orbit around the earth create a map of the intensity of greenhouse gasses. Additionally, introduction of sensors near exhaust pipes provides collectible data. Using the obtained data, it is possible to monitor the concentration of gasses and identify the causes of their occurrence. 

As measures to combat high emissions, carbon credits and carbon farms have been developed. Farms are green spaces designed for intensive absorption of greenhouse gasses. Credits, on the other hand, represent a currency equal to a certain number of tons of emitted gasses and are intended for enterprises that produce greenhouse gasses.

How is the cooperation organized?

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  1. 1. Getting to know a partner.

 

  1. 2. Consult and decide on the project.

 

  1. 3. Select the optimal source of financing: grants, exim banks, etc.

 

  1. 4. Receive funding and connect the top experts in the industry.

 

  1. 5. In 8-12 months, the project is launched. 
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