Analyzing Imprecise Data from Wireless Temperature Sensor
Usama Afzal Β· Muhammad Aslam Β· Muhammad Ahmed Shehzad Β· Florentin Smarandache
Infinite Study
ΠΠ»Π΅ΠΊΡΡΠΎΠ½Π½Π°Ρ ΠΊΠ½ΠΈΠ³Π°
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ΠΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΡΡΡΠ°Π½ΠΈΡ
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ΠΠΎΠΆΠ½ΠΎ Π΄ΠΎΠ±Π°Π²ΠΈΡΡ
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reportΠΡΠ΅Π½ΠΊΠΈ ΠΈ ΠΎΡΠ·ΡΠ²Ρ Π½Π΅ ΠΏΡΠΎΠ²Π΅ΡΠ΅Π½Ρ. ΠΠΎΠ΄ΡΠΎΠ±Π½Π΅Π΅β¦
ΠΠ± ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΠΎΠΉ ΠΊΠ½ΠΈΠ³Π΅
Various sensors play an important role in the monitoring and development of robotic technology. We present a contemporary statistical analysis method for evaluating datasets generated by robotic systems. Specifically, this data set originates from the physical structure of the robot and is acquired by a wireless temperature sensor. The data collection process spans a temporal period of 1 to 10 hours during the operational period of the robot. The collected data is subjected to a rigorous analysis using neutrosophic methodology. To facilitate this, a modern neutrosophic formula has been devised, drawing on definitions established within the field. To benchmark the effectiveness of the proposed approach, a conventional formula is also used for comparison purposes. Our results clearly indicate that the proposed method achieves higher levels of information richness and adaptability compared to classical methods. This indicates the improved utility of the proposed approach in solving the complexities of robotic data analysis.
ΠΡΠ΅Π½ΠΈΡΠ΅ ΡΠ»Π΅ΠΊΡΡΠΎΠ½Π½ΡΡ ΠΊΠ½ΠΈΠ³Ρ
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ΡΠΎΠ½ΠΈΠ·ΠΈΡΡΠ΅ΡΡΡ Ρ Π²Π°ΡΠΈΠΌ Π°ΠΊΠΊΠ°ΡΠ½ΡΠΎΠΌ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈ, ΠΈ Π²Ρ ΡΠΌΠΎΠΆΠ΅ΡΠ΅ ΡΠΈΡΠ°ΡΡ Π»ΡΠ±ΠΈΠΌΡΠ΅ ΠΊΠ½ΠΈΠ³ΠΈ ΠΎΠ½Π»Π°ΠΉΠ½ ΠΈ ΠΎΡΠ»Π°ΠΉΠ½ Π³Π΄Π΅ ΡΠ³ΠΎΠ΄Π½ΠΎ.
ΠΠΎΡΡΠ±ΡΠΊΠΈ ΠΈ Π½Π°ΡΡΠΎΠ»ΡΠ½ΡΠ΅ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΡ
Π‘Π»ΡΡΠ°ΠΉΡΠ΅ Π°ΡΠ΄ΠΈΠΎΠΊΠ½ΠΈΠ³ΠΈ ΠΈΠ· Google Play Π² Π²Π΅Π±-Π±ΡΠ°ΡΠ·Π΅ΡΠ΅ Π½Π° ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ΅.
Π£ΡΡΡΠΎΠΉΡΡΠ²Π° Π΄Π»Ρ ΡΡΠ΅Π½ΠΈΡ ΠΊΠ½ΠΈΠ³
Π§ΡΠΎΠ±Ρ ΠΎΡΠΊΡΡΡΡ ΠΊΠ½ΠΈΠ³Ρ Π½Π° ΡΠ°ΠΊΠΎΠΌ ΡΡΡΡΠΎΠΉΡΡΠ²Π΅ Π΄Π»Ρ ΡΡΠ΅Π½ΠΈΡ, ΠΊΠ°ΠΊ Kobo, ΡΠΊΠ°ΡΠ°ΠΉΡΠ΅ ΡΠ°ΠΉΠ» ΠΈ Π΄ΠΎΠ±Π°Π²ΡΡΠ΅ Π΅Π³ΠΎ Π½Π° ΡΡΡΡΠΎΠΉΡΡΠ²ΠΎ. ΠΠΎΠ΄ΡΠΎΠ±Π½ΡΠ΅ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΌΠΎΠΆΠ½ΠΎ Π½Π°ΠΉΡΠΈ Π² Π‘ΠΏΡΠ°Π²ΠΎΡΠ½ΠΎΠΌ ΡΠ΅Π½ΡΡΠ΅.
