Academic literature on the topic 'ESP32-based core'

Abstract Fluid systems play a crucial role with respect to economic and societal interests, and their increasing complexity demands intelligent control concepts for efficient operation. Conventional control approaches have limitations, making distributed control, based on so-called agents, a promising solution. In distributed control an agent is allocated to a component of the fluid system. Utilizing sensors and actuators the agent perceives and manipulates its surrounding. Furthermore, the exchange of information between agents is crucial to this control method. This paper presents the physical implementation of two agent-based controllers into a test rig for distributed water supply systems, focusing on the hardware components needed. The considered fluid system comprises several active and passive components like pumps and valves, respectively. As a first step, a pump and a valve are equipped with an agent. A minimal example of distributed control is presented in which the volumetric flow rate through the valve is measured by a sensor and shared with the pump agent, which then controls the pump’s speed accordingly. To enable this, the agent must have suitable rotational hardware interfaces to connect sensors and actuators and facilitate communication with other agents. At the core of each agent lies an ESP32 microcontroller, which operates as a discrete PID controller and enables web-based communication for data exchange.

This research presents the development and evaluation of a prototype AI-powered glasses attachment designed to enhance the daily mobility and independence of individuals with visual impairments. The work addresses the significant challenges faced by millions who experience limitations in navigating, recognising objects, and accessing information. It aims to contribute to the field of assistive technologies by creating a cost-effective and versatile solution. The project emphasises the importance of designing inclusive technology that is not only functional but also user-friendly and accessible to all. The system has several strengths:* Compact and portable design making it a discrete companion in daily life.* Versatile functionality combining object/text recognition with speech interaction.* Cost-effective approach making it accessible to a broader range of users.The core of the prototype integrates real-time object and text recognition, along with speech interaction capabilities. The system uses image processing algorithms, particularly convolutional neural networks (CNNs) to identify objects. Optical character recognition (OCR) is implemented to transform printed text into digital formats, enabling text-to-speech functionality. The prototype also incorporates a natural language processing (NLP) powered chatbot, facilitating spoken interaction and information retrieval. The project involved a thorough analysis of user requirements, focusing on the needs of individuals with varying degrees of visual impairment. This included understanding the challenges faced by people with different levels of sight loss, from moderate to complete blindness. The study also highlighted the importance of intuitive design and accessibility. The hardware design incorporates a compact ESP32-S3 microcontroller coupled with an OV5640 camera module, chosen for their balance of performance and power efficiency. The software is developed using Python for data processing and C++ for the microcontroller. Cloud-based AI services, including Google Cloud Text-to-Speech API and OpenAI's GPT API and Whisper API, are used for text-to-speech, object and text recognition, and speech recognition, respectively. The 3D-printed enclosure for the attachment was designed with several key considerations, including compactness, component integration, and user comfort. Key aspects of the hardware design are:* Component Layout: The enclosure was designed to house the ESP32 microcontroller, the OV5640 camera module, and a TTP223B touch sensor. The internal structure includes a separate compartment for the camera with a heatsink to manage its operating temperature.* Touch Sensor Integration: The touch sensor is located on the underside of the enclosure, designed with a concave depression for easy access and covered with a rubber membrane. This placement allows for user interaction and control of the system’s functions.* Size and Weight: The prototype has a weight of 23 grams. Its design aimed to be as small as possible whilst being able to accommodate the necessary hardware.The conducted functional tests focused on the accuracy of text and object recognition, and the efficacy of the chatbot. The text and object recognition performed well, however, issues with the camera quality, particularly in low-light conditions, limited the system's performance with smaller details and text. The speech interaction, while functional, encountered some difficulties with complex questions. The prototype is promising, future development should focus on addressing its limitations. Potential improvements include an automated configuration process, the integration of a navigation system and a more robust camera. Enhancing the user interface with a more tactile feedback system could improve accessibility.

This work deals with the development of a control device for an active filter based on an ESP32 microcontroller. The main goal of the development is the effective compensation of harmonic distortions in electrical networks that arise under the influence of non-linear loads. The paper describes in detail the circuits of voltage and current sensors used to monitor network parameters, as well as their integration with ESP32 for data collection. Voltage and current sensors play a key role in ensuring the accuracy of filter control. Their circuits include precision resistive dividers to measure voltage and Hall sensors to measure current. As a result of receiving signals from these sensors, an analog signal is generated, which is converted into a digital one using the built-in ESP32 ADC. Special attention is paid to the analysis of signal diagrams from sensors that demonstrate changes in electrical parameters in real time. This ensures quick response of the system to changes in the load and effective control of the active filter. ESP32 performs the generation of a PWM signal, which serves to control the inverter of the active harmonic filter. The work considers the methods of generating PWM signals that ensure the minimization of harmonic distortions in the network. The generation of PWM signals takes place using a 16-bit generator, which allows for high accuracy and smooth control of voltage and current with the help of an inverter. Features of setting the frequency and pulse width for adaptation to changing operating conditions of the active filter control device are also given. The algorithm for converting signals from sensors is based on high-speed reading of analog signals, their filtering and processing to form control actions. To ensure the operation of the power active filter control device, software code is used, which allows the system to simultaneously read data, generate a control signal and monitor network parameters. The results of this study can be used in industrial systems and household networks to improve the quality of electrical energy by actively compensating harmonic distortions.

Vertical farming, a revolutionary approach to agricultural production, has gained significant attention in recent years due to its potential to address various challenges facing traditional farming practices. This paper provides a comprehensive overview of IoT-based Vertical Farming systems, exploring their hardware design, implementation strategies, testing methodologies, and prospects.The hardware design of IoT-based Vertical Farming systems encompasses a range of components essential for creating optimal growing environments. Soil moisture sensors, temperature and humidity sensors, light-dependent resistors (LDRs), and ESP32 Wi-Fi modules are among the key elements utilized in these systems. Soil moisture sensors enable precise irrigation management by measuring water content in the soil, while temperature and humidity sensors provide insights into environmental conditions. LDRs detect light levels, facilitating optimal lighting control, and ESP32 Wi-Fi modules enable wireless communication for remote monitoring and control.Implementation strategies for IoT-based Vertical Farming systems involve hardware setup, software development, and integration with existing infrastructure. Sensor nodes distributed throughout the farming environment are connected to a central control unit via Wi-Fi or other communication protocols. Software interfaces and applications are developed to provide users with real-time monitoring and control capabilities, allowing them to adjust environmental parameters as needed.Effective testing methodologies are crucial for ensuring the reliability, functionality, and security of IoT-based Vertical Farming systems. Black box testing focuses on external functionality, such as user interface interactions and sensor responses, while white box testing examines internal system components and code logic. Grey box testing combines elements of both black and white box testing, with a focus on limited knowledge and system behavior.The future prospects of IoT-based Vertical Farming are promising, with opportunities for innovation and advancement. Research and development efforts are needed to enhance system scalability, energy efficiency, and data analytics capabilities. Integration with artificial intelligence (AI) and machine learning (ML) algorithms can enable predictive analytics and autonomous decision-making, optimizing crop production and resource utilization. Expanding the application of vertical farming to diverse environments, including urban areas and arid regions, can address global food security challenges and promote sustainable agriculture practices.In conclusion, IoT-based Vertical Farming represents a transformative approach to agriculture, offering scalable and sustainable solutions to meet the growing demand for food production. Continued research, development, and adoption of these systems have the potential to revolutionize the agricultural industry and contribute to a more food-secure and environmentally sustainable future.