In workspaces and commercial buildings, lighting represents a significant portion of energy consumption after HVAC systems. However, current lighting solutions often lack efficiency and fail to adapt to occupancy levels and varying lighting needs. There is a need for an intelligent lighting system that can reduce energy consumption while maintaining occupant comfort by automatically adjusting lighting intensity based on occupancy and natural light levels.

Finding precise answers to questions within given articles is a challenge that existing systems struggle to address. There is a need for an AI-driven question answering technology that can automatically extract short spans of text as precise answers from articles.

Consensus in distributed ledger technology is often limited by the blockchain trilemma, which encompasses data size, consensus speed, and network security. In this context, we present a leaderless quantum consensus algorithm that utilizes quantum simulators and real quantum computers for a simplified consensus scenario.

Fine-grained and personalized monitoring of gym exercises is essential for users to track their progress, improve their routines, and prevent injuries. There is a need for a cost-effective and unobtrusive technology that provides accurate insights into multiple aspects of gym exercise behavior.

Indoor location tracking is a valuable capability for various applications, but existing solutions often require costly infrastructure investments or have limited compatibility with specific devices. There is a need for an indoor location system that works seamlessly with existing Wi-Fi infrastructure, without requiring additional costs or device-specific limitations.

Researchers in healthcare and retail domains face challenges in capturing and analyzing personalized lifestyle data. Existing approaches require manual effort or extensive infrastructure deployment, resulting in inefficiency and privacy concerns. There is a need for a technology that reduces human effort and privacy concerns while capturing and analyzing personalized lifestyle data. 

Obesity rates have tripled since 1975 and are projected to reach 15% of the global and Singaporean population by 2024. Existing health and fitness apps have limitations, failing to make a long-term difference for users. Customers often opt out due to data input requirements, lack of personalization, and the non-motivating nature of the apps.