Search results for: 'energy and power systems technology'

Energy harvesting sensor solutions are emerging as a foundational layer for large-scale ambient IoT, enabling autonomous, battery-free sensing across distributed and infrastructure-intensive environments. By converting ambient energy sources such as light, heat, vibration, and RF into usable power, these sensors eliminate the need for wired power a...

The rapid expansion of Internet of Things (IoT) ecosystems has intensified the demand for uninterrupted, autonomous sensing solutions that can operate without reliance on conventional batteries. This research study investigates the evolving landscape of self-powered sensors as a foundational technology for next-generation, batteryless IoT—particula...

The Microelectronics Technology Opportunity Engine covers innovations pertaining to SiC Power Modules, AI SoCs, GaN, Edge AI and Photonics among others.The Microelectronics Technology Opportunity Engine captures global electronics-related innovations and developments on a weekly basis. Developments are centered on electronics attributed by low po...

This study examines the technology landscape, commercialization progress, and future growth opportunities of wide-bandgap (WBG) semiconductor materials, with a primary focus on silicon carbide (SiC), gallium nitride (GaN), and gallium oxide (Ga₂O₃) for power and RF electronics. It evaluates how these materials enable higher efficiency, greater powe...

The Microelectronics Technology Opportunity Engine covers innovations pertaining to Sub-1 Nm Chip technology, MMIC, SOC, Photonic Chiplet, GaN and Power Electronics among others.The Microelectronics Technology Opportunity Engine captures global electronics-related innovations and developments on a weekly basis. Developments are centered on electron...

Multimodal sensor fusion is an advanced perception technology that combines data from multiple sensors, including cameras, LiDAR, radar, ultrasonic sensors, thermal cameras, and inertial measurement units (IMUs), to give robots and autonomous systems a more accurate, reliable, and comprehensive understanding of their environment. It overcomes the l...

This study examines the emerging landscape of neuromorphic computing and its role in enabling low-power, real-time, brain-inspired intelligence across edge and autonomous systems. It reviews advancements in spiking neural networks, memristor-based computing in memory, event-driven vision sensors, and hybrid neuromorphic and conventional architectur...

Hybrid vision systems (HVS) are positioned to substantially impact perception-driven applications across a diverse array of sectors, including robotics, manufacturing, logistics, mobility, surveillance, and agriculture. By intricately combining the geographical precision of LiDAR with the semantic intelligence of advanced imaging systems, these inn...

The Microelectronics Technology Opportunity Engine covers innovations pertaining to Microcontrollers, Low Power MCU’s, GaN and AI Interconnects.The Microelectronics Technology Opportunity Engine captures global electronics-related innovations and developments on a weekly basis. Developments are centered on electronics attributed by low power and co...