The sheer volume of reads (e.g., in a smart warehouse generating millions of tag events per hour) creates a big data challenge. Filtering false positives (ghost reads), missing reads, and noisy RSSI values requires complex middleware. Real-time analytics, especially when integrating RFID with other IoT sensors, demands efficient stream processing algorithms.
RFID performance degrades severely near metals (detuning) and liquids (signal absorption). Although on-metal tags and near-field solutions exist, no universal tag works equally well on all materials. Environmental factors like humidity, temperature, and multipath fading in indoor industrial settings continue to challenge reliability. RFID Systems- Research Trends and Challenges
The power bottleneck is being addressed through ambient backscatter communication, where tags reflect existing TV, Wi-Fi, or cellular signals rather than generating their own. This enables battery-free, ultra-low-power devices. Concurrently, research into hybrid energy harvesters (RF + solar + vibration) is extending the operational life of active and semi-passive tags. The sheer volume of reads (e
