AI-Powered Smart Bassinet with Multi-Sensor Integration and Real-Time Personalized Infant Care Recommendations

Smart overview of the Invention

The AI-powered smart bassinet integrates multiple sensors to monitor both environmental conditions and the physiological parameters of an infant. These sensors are strategically positioned beneath and beside the baby to gather comprehensive data. A neural network processes this information to generate personalized recommendations for improving infant sleep, which are communicated to caregivers through an interactive graphical user interface. This interface also allows caregivers to provide feedback, enhancing the system's adaptability and effectiveness.

Technical Features

To ensure data security and continuous improvement, the system employs federated learning, which processes data locally while contributing to a broader network of devices. This approach enhances privacy by avoiding centralized data storage. The bassinet's dual API architecture facilitates secure on-device data processing and enables encrypted data sharing with third-party developers. This open ecosystem encourages innovation in infant care by allowing external applications to interact with the system.

Innovative Approach

Unlike traditional monitoring devices, this bassinet leverages advanced AI and machine learning techniques to provide real-time, actionable insights. By utilizing crowd-sourced data and multi-source learning, the system offers more accurate and personalized recommendations than existing solutions. The integration of IoT capabilities further distinguishes this bassinet by enabling remote monitoring and control, thus addressing common parental concerns about infant sleep safety and health.

Comparative Analysis

Existing patents in the field of infant sleep devices primarily focus on sensory stimuli or basic monitoring functions without addressing underlying sleep issues. In contrast, this smart bassinet not only monitors but also analyzes a wide range of physiological data to offer personalized care strategies. By incorporating federated learning and APIs, it significantly enhances data processing capabilities while maintaining robust privacy standards, setting a new benchmark for infant care technology.

Applications and Benefits

The proposed system can be integrated into various infant care devices like bassinets, cribs, or incubators, providing a holistic approach to managing an infant's sleep routine. It offers caregivers real-time insights into factors affecting sleep such as feeding times, mood, and environmental conditions. The intuitive graphical user interface simplifies the presentation of these insights, helping caregivers adopt optimal practices for infant care. This comprehensive approach not only improves sleep patterns but also contributes positively to overall infant health.