RFID Contextual Location for Wi-Fi Power Adjustment
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Solution Overview
Problem
Portable devices, such as mobile phones and tablets, experience unnecessary battery drain due to Wi-Fi transceivers remaining active even when not connected to a wireless network, consuming power while seeking available connections.
Innovation Solution
Implementing an RFID system that activates and deactivates Wi-Fi transceivers based on proximity to RFID tags, optimizing antenna power based on signal strength, using a learning algorithm to manage power consumption by connecting and disconnecting from wireless networks only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the Wi-Fi transceiver remains active to maintain network connectivity, then communication reliability is improved, but battery power consumption increases
Solution Approach 1:
The Wi-Fi transceiver is activated periodically based on detected RFID tags rather than remaining continuously active. The system scans for RFID tags at intervals and activates the transceiver only when tags are detected, converting continuous operation into periodic operation to reduce power consumption while maintaining connectivity when needed.
Solution Approach 2:
The system uses RFID tags placed in the environment to automatically trigger transceiver activation. When an RFID tag is detected, the system self-activates the Wi-Fi transceiver without user intervention, and deactivates it when tags are no longer detected, enabling the system to serve itself based on environmental conditions.
2Adaptability or versatility
If the Wi-Fi transceiver actively seeks network connections, then network availability is improved, but battery power is unnecessarily drained
Solution Approach 1:
RFID tags are pre-placed in locations where Wi-Fi networks are available. The system scans for these tags in advance and uses their presence as a trigger to activate the transceiver, eliminating the need for continuous network scanning and connection attempts, thereby reducing energy loss while maintaining network availability when needed.
Solution Approach 2:
RFID tags serve as intermediary indicators of network availability. Instead of directly scanning for Wi-Fi networks continuously, the system uses RFID tags as mediators that indicate where networks are available, triggering transceiver activation only when these intermediary signals are detected.
3Reliability
If antenna power is increased to maintain strong signal, then signal strength is improved, but power consumption increases
Solution Approach 1:
The antenna power is made dynamic rather than static. The system adjusts antenna power levels based on detected signal strength and RFID tag presence, increasing power when strong signals are needed for reliability and decreasing power when signals are adequate or the transceiver is inactive, thereby optimizing the balance between signal strength and power consumption.
Solution Approach 2:
The system changes the power parameter of the antenna based on environmental conditions and signal requirements. By adjusting the power parameter dynamically according to detected RFID tags and signal strength measurements, the system maintains adequate signal strength while minimizing unnecessary power consumption during low-activity periods.
Data Source
AI summary
In embodiments of RFID-based location determination for antenna power adjustment, a mobile device includes a RFID reader to interrogate and communicate with RFID tags. A control module can utilize a learning algorithm to determine a current location of the mobile device based on physical locations associated with the RFID tags, and an antenna power of a wireless transceiver can be adjusted for a signal strength of a wireless network based on the current location of the mobile device. The learning algorithm can maintain a database that includes information about particular locations or rooms within a residence, the signal strength of wireless networks at the locations, and identifiers of the RFID tags. The learning algorithm can learn context of a user's location with the mobile device to improve utilization of the antenna power of the wireless transceiver, and conserve battery power of the mobile device.