Budowa Silesia Photonics (BWS PHOTONICS) designs and manufactures passive optical components, PLC splitters, AWG, FBT couplers, optical circulators, isolators, ROADM, MPO patching, FTTH ODN, and BESS-...
HOME / Low Loss Detector for IoT Applications - Budowa Silesia Photonics
This TI Design uses Texas Instruments'' nano-power operational amplifier and the SimpleLinkTM multi-standard 2.4-GHz wireless microcontroller (MCU) platform to demonstrate an ultra-low-power motion
Edge computing, a key component of Internet of Things (IoT) systems, enables data processing close to the data source. In low-power, resource-constrained IoT environments, it can
Designing such lightweight object recognition models is more difficult than ever due to the growing demand for accurate, quick, and low-latency models
This paper begins with a summary of the detection methods and applications, accompanied by a discussion of the categorization of IoT anomaly detection algorithms.
To address these challenges, we propose an improved neck structure, SRB-FPN, to achieve fine-grained cross-level semantic alignment and feature fusion, while also optimizing the regression loss
Discover ST''s iNEMO 6-axis inertial measurement units (IMU) for motion tracking and gesture detection in smartphones, wearables, TWS and IoT connected devices.
Discover the full range of LoRaWAN IoT devices from ioX-Connect, engineered for reliable, long‐range, low‐power connectivity.
This paper proposes a lightweight framework that combines classical signal processing techniques (Fourier and Wavelet-based feature extraction) with edge-deployed machine learning
This paper proposes a lightweight framework that combines classical signal processing techniques (Fourier and Wavelet-based feature extraction) with
Designing such lightweight object recognition models is more difficult than ever due to the growing demand for accurate, quick, and low-latency models for various edge devices. The most
YOLO26 from Ultralytics delivers faster, simpler, end-to-end NMS-free object detection optimized for edge and low-power devices.
We present a systematic comparison of the models derived from both strategies, all designed under shared hardware constraints, and tailored for deployment on IoT gateway platforms.