The first step is to understand the needs and requirements of the client. In the case of this application, it is important to know what functionalities are expected of it, such as displaying information about the state of the litter box, remote device control, usage monitoring, and so on.

Understanding customer requirements

Next, we conduct a market analysis to understand competitive applications and what features are already available. In this step, we also evaluate what features can help differentiate in the market and propose the best solutions to meet customer requirements.

Market analysis

During the execution of this project, we encountered a challenge related to processing large amounts of data transmitted by thousands of devices per second. To meet this challenge, we had to pay particular attention to aspects such as security, data analysis and aggregation, system architecture, scalability, and many others. Thanks to the hard work and perseverance of our team, we were able to achieve satisfactory results and we are proud of the success we have achieved.

Challenge

Prototyping and designing

Programming and testing

Project deployment

**We have completed a project to create an advanced mobile application for pet lovers. The application enables users to remotely manage devices used for pet care, as well as providing access to knowledge and tools necessary for effective pet care.** 

The project was completed based on a comprehensive solution that combines electronics, mechanics, a mobile application, and an administrative panel for device operators and sellers. Our main goal was to enable pet owners to remotely manage the care of their beloved pets.

Due to the diversity of product users, we decided to introduce the application on both iOS and Android platforms. We achieved this using tools that support both platforms simultaneously, thereby significantly lowering the project cost. Taking into account the wide range of audiences speaking different languages, we decided to use a tool that allows for easy introduction of additional languages without interfering with the application code.

Mobile application and service for managing IoT devices

mobile-application-and-service-for-managing-iot-devices

###### **The goal of the project was to develop an electronic circuit with a Kintex 7 FPGA and QSFP connectors capable of 40 Gbps data transmission.**
As part of the project, an electronic system was developed based on a 12-layer printed circuit board equipped with two QSFP connectors, each operating at a speed of 40 Gbps. The main component in this system is an FPGA called Kintex7, which allows for programming of the system's functionalities.

The system was designed with applications that require high data throughput and programmability in mind. With the use of the Kintex7 FPGA and fast QSFP connectors, the project enables fast data transmission in high-performance networks such as data centers and servers. At the same time, the ability to program the FPGA opens up a wide range of possibilities for customizing the system for different applications and requirements, making the project universal and scalable.



Electronic system for high-frequency data transmission

electronic-system-for-high-frequency-data-transmission

The project cost 200,000 PLN and was financed by IDUB PW. The fund was allocated for designing a fluid mixer with cross activation using machine learning techniques.

For whom

Starting the design process, we used machine learning algorithms to create a model of the behavior of a fluid mixer. This model is trained on a dataset of known input and output parameters, such as flow rate, fluid viscosity, mixer geometry, and mixing efficiency. Once we obtained the model, we used it to explore the design space and optimize the mixer's performance. We can use techniques such as Bayesian optimization or genetic algorithms to search for the best combination of input parameters, such as cross-activation frequency, mixer blade angle, and flow rate.

By utilizing machine learning to assist in the design process, we can efficiently explore a vast design space and quickly identify optimal solutions. This approach can lead to the development of highly efficient fluid mixers that can be tailored to specific industrial applications.

The technology developed during the project has a wide spectrum of applications in areas where small and accurate representations of large data for future state predictions are needed. The most popular applications are:
Wind turbine industries
Computer vision-based technologies

Application

Prototyping and development

Application deployment

**In the project, we used deep neural network learning for the reduced order embedding for representing the dynamics of the flow system.** 

We used reduced order embedding for training and predicting the flow in future flow time and obtained 2 orders of magnitude reduction in computational run times. We developed technology for reduced order modeling of complex processes, which generates a large amount of data.

The technology developed during the project can be used for the prediction or generation of video frames using small computational costs.


Machine Learning assisted design of a laminar fluid mixer with spanwise actuation

machine-learning-assisted-design-of-a-laminar-fluid-mixer-with-spanwise-actuation

###### **We have developed a project of an intelligent module kit for toys of the future. The project was carried out from concept to a finished product. The implementation of the project included user needs analysis, feasibility study, electronic circuit design, enclosure design, and preparation of the project for laboratory testing.**

The module sets were used in educational robots, enabling the acquisition of knowledge in future professions such as programming/engineering, all in the form of a game/toy. The product was primarily aimed at children and youth without prior experience.


The set of smart modules

the-set-of-smart-modules

We use RFID technology for bin identification and image recognition algorithms for waste segregation verification.


What technologies are used?

The system monitors bins for the presence of dangerous substances, such as gas or radioactive materials, and alerts in case they are detected.

What safety measures are implemented?

The portal allows for device monitoring, downloading statistics, sending configurations to devices, and verifying the status of garbage bins and vehicles.

What functions does the client portal offer?

System Design and Component Selection

Development and Programming

System Testing and Adjustments

**Readiy Technology House is engaged in creating an innovative mechanism for municipal waste management devices that identify garbage bins in real time and use a camera and specialized algorithms to check if waste has been properly segregated. Information about lifted bins, such as weight, time, geographical coordinates, and various other system status data, are transmitted via cellular network to a database. This innovative waste analyzing and IoT device management platform is aimed at the public sector and has tremendous potential for integration with other systems.**

Along with the platform, we create a web portal for customers, which enables continuous control over all devices, downloading lists and statistics, sending appropriate configurations to devices, as well as full control and verification whether a given bin should be emptied or not, where a given vehicle is located, and if everything works correctly.

Our platform is compatible with various mobile devices, such as smartphones, tablets or laptops, which is extremely important in today's world, when more and more users access the Internet via mobile devices.

Work on this project started in 2021. The initial phase was the selection of appropriate components to create the entire system, and then the construction of a lift simulator lifting bins. The next step was to program all elements and select the appropriate software.
Our system offers many capabilities and configurations depending on the customer's needs. It allows identification of each bin using a unique RFID chip, weighing waste during emptying of the container, constant monitoring of vehicle positions, taking pictures of the contents of the bin, which are transmitted to the server and verified there by the program and an algorithm that catches improper objects that should not be in the given bin. It also ensures safety, alerting of any dangers such as fire, gas, or radioactive substances.

Considering the experience and innovative technologies, Readiy Technology House offers thoughtful and effective design. Guided by understanding customer needs, we design and create solutions that respond to their requirements.

Intelligent Waste Management System

intelligent-waste-management-system

It allows farmers to monitor the condition of poultry houses in real time, leading to more efficient management and improved poultry welfare.

What are the key benefits for poultry farmers using this technology?

Absolutely, one of our main goals was to create an intuitive application tailored to all users.

Is the app suitable for people without technical experience?

We plan to further develop the technology, including expanding the range of monitored parameters and improving data processing algorithms.

What are the future directions of development?

Development of project concept and strategy

Design and Prototyping

Implementation and Integration

Testing and Implementation

Support and Optimization

**We are proud to introduce Innovative Photocatalytic Technology (RCI) dedicated to poultry houses. Our solution focuses on improving poultry welfare and effectively monitoring and reducing pollutants such as dust and ammonia.**

The main component of the project is an application that collects data from sensors deployed in poultry houses. These are presented in an easily digestible form that is tailored to the needs of poultry farmers. Each poultry house is equipped with sensors from four categories, and data is collected from them, from which an average is calculated.

In addition to the application itself, our team worked on the system architecture, ensuring stability and reliability on our servers. We also put in place a process to enable efficient communication between the devices and the application.

Machine learning

Python