Handheld tourist guidance system using GPS

Hema, L. K.; Indumathi, R.; Prabhakaran, Vivek; Kumari, Dipti

doi:10.1016/j.matpr.2021.04.561

Cited by 3 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It may reduce time-to-first-fix (TTFF) to less than 1 second because of its 50 channels of positioning engines [20]. For communication, this module has a patch antenna with a sensitivity of 161 dBm [21]. It is used in the proposed system to get the location and speed of EVs because the GPS module operates at 3.3 v; it is powered by ESP32 by using two pins in ESP32 (3.3 V, GND), as shown in Figure 4.…”

Section: Gps Module Neo 6mmentioning

confidence: 99%

Internet of things based real-time electric vehicle and charging stations monitoring system

Mohammed

Qahtan

Ali

2022

IJEECS

View full text Add to dashboard Cite

Due to a shortage of fuel sources and the increment in environmental pollution, efficient techniques should be introduced. The best solution is to move to the use of electric vehicles. The article aims to develop a solution for electric vehicle (EV) charging station locations that utilize the internet of things (IoT) technology. The IoT is a paradigm that uses sensors and transmitting networks to provide current facilities with a real-time global communication perspective of the physical world. This paper proposes a real-time system to provide a real-time update to EV location and charging stations (CSs) location to reduce time lost by users searching CSs, and provides real-time charging station (CS) recommendations for EV users by displaying the nearest CS, provide estimation arrival time to the nearest CS, display distance between nearest CS and EV real-time updated. The work of the proposed system was tested, and the most significant error rate (17 meters) is represented by the difference in the distance obtained from the system and the distance obtained from Google Map. The total accuracy of the design for the tested case is (98.014%).

show abstract

Section: Gps Module Neo 6mmentioning

confidence: 99%