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In most real-time scenarios such as emergency first response or a patient self-monitoring using a wearable device, it is likely that accessing a healthcare physician for assessing potential vital sign anomalies and providing a recommendation will be impossible; thus potentially putting the patient at risk. Leveraging the latest advances in Natural Language Processing (NLP), this study presents a research-driven design and development of a cloud-based conversational AI platform trained to predict vital signs anomalies and provides recommendations from a dataset created by physicians.
To reinforce the learning of the virtual assistant, the Conversation Driven Development (CDD) methodology has been adopted to involve end users in the testing process in the early phase. The proposed platform will help to manage the consequences of low physician-patient ratios, especially in developing countries.
Noise pollution is a significant yet often overlooked environmental issue, impacting millions of people daily. Common health problems resulting from noise pollution include hearing loss, high blood pressure, heart diseases, sleep disturbances, stress, and headaches. The challenge in mitigating no...
In the modern era of smart technology, efficient waste management is a significant concern, particularly in urban areas. This project introduces an innovative smart dustbin system designed to enhance hygiene, convenience, and efficiency in waste disposal. The core of the system is an ESP8266 micr...
Urban gardening has become increasingly popular as city dwellers seek to grow their own food and green their living spaces. However, managing an urban garden efficiently can be challenging due to space constraints and the need for continuous monitoring and care. The Smart Urban Gardening System a...
The Smart Truck Bed Cover System integrates ESP8266 technology with various components to create an automated and responsive solution for truck bed covers. This project utilizes a servo motor, buzzer, LED indicators, tent cover, and rain sensor to enhance usability, protection, and convenience for t...
The Conveyor Belt Control System with ESP8266 and Servo Motor is an advanced project designed to automate the control, monitoring, and sorting of items on a conveyor belt. This system uses the ESP8266 Wi-Fi module for wireless communication, enabling remote management and real-time monitoring of con...
This IoT-based conversational AI Recommender assistant for vital sign predicted anomalies project can be implemented using components available at SoftTech Supply (STS) in Kigali, Rwanda. Whether you need Arduino boards, Raspberry Pi, ESP32, ESP8266, sensors, microcontrollers, or any other electronic components, we have everything in stock. STS provides complete project support including component selection, circuit design, programming assistance, and troubleshooting. Our team can help you implement this project from start to finish. Visit our electronics shop or contact us for personalized consultation. We serve students, hobbyists, and professionals across Rwanda with quality components and expert technical support.