IoT-Based Employee Location Tracking with Google Maps using STM32 and ESP Microcontroller- A Technological Comparison
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Abstract:
An employee tracking system helps to track real-time employees' activities inside and outside the premises. The system helps us improve the productivity and efficiency of the work, mainly for the employee who does the traveling job. The designed product can be implemented in schools and colleges to track employees' activities. The cost-effective prototype is technologically advanced using GPS Neo-6 Module and 32-bit Microcontrollers, which must be carried by the employee regularly. The prototype design can easily connect to the Wi-Fi, display the longitude and latitude on the OLED display, Web Brower, and then display the location on Google Maps. The Google map information can show the employee's real-time location and can be accessed anywhere. At last, the prototypes developed are compared in terms of the development cost. Further work is to incorporate tracking the fitness of the employee.Keywords:
STM32
Geographic coordinate system
Geolocation
Tracking (education)
Tracking system
Microcontroller is widely used in the intelligent life of modern society. Intelligent development based on Microcontroller to solve the actual needs of people’s life, work, study and other fields is the core of Microcontroller application. Therefore, it is a task for researchers to understand the structure and performance of microcontroller, develop software, and be familiar with the method and process of intelligent development based on microcontroller. And with that in mind, this paper designs and produces a physical hardware system for indoor environment detection based on STM32 microcontroller. The system can detect the light intensity, temperature and humidity, and CO gas concentration in the indoor environment; and the data is integrated and processed by the STM32 microcontroller to display the current parameter values of each quantity in the indoor environment on a 3.5-inch resistive screen; at the same time, the PC can also log in to the OneNET cloud platform through the web page, and display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time in the device created by OneNET for real-time viewing. The system can also display the light intensity, temperature and humidity, and CO gas concentration values in the indoor environment in real time. The hardware system has been tested and tested to achieve its function.
STM32
Light intensity
Resistive touchscreen
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Geolocating social media posts relies on the assumption that language carries sufficient geographic information. However, locations are usually given as continuous latitude/longitude tuples, so we first need to define discrete geographic regions that can serve as labels. Most studies use some form of clustering to discretize the continuous coordinates (Han et al., 2016). However, the resulting regions do not always correspond to existing linguistic areas. Consequently, accuracy at 100 miles tends to be good, but degrades for finer-grained distinctions, when different linguistic regions get lumped together. We describe a new algorithm, Point-to-City (P2C), an iterative k-d tree-based method for clustering geographic coordinates and associating them with towns. We create three sets of labels at different levels of granularity, and compare performance of a state-of-the-art geolocation model trained and tested with P2C labels to one with regular k-d tree labels. Even though P2C results in substantially more labels than the baseline, model accuracy increases significantly over using traditional labels at the fine-grained level, while staying comparable at 100 miles. The results suggest that identifying meaningful linguistic areas is crucial for improving geolocation at a fine-grained level.
Geolocation
Geographic coordinate system
Granularity
Tree (set theory)
Baseline (sea)
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Assigning semantically relevant, real-world locations to documents opens new possibilities to perform geographic information retrieval. We propose a novel approach to automatically determine the latitude-longitude coordinates of appropriate Wikipedia articles with high accuracy, leveraging both text and metadata in the corpus. By examining articles whose base-truth coordinates are known, we show that our method attains a substantial improvement over state of the art works. We subsequently demonstrate how our approach could yield two benefits: (1) detecting significant geolocation errors in Wikipedia; and (2) proposing approximated coordinates for hundreds of thousands of articles which are not traditionally considered to be locations (such as events, ideas or people), opening new possibilities for conceptual geographic retrievals over Wikipedia.
Geolocation
Geographic coordinate system
Geotagging
Longitude
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STM32
Electronic design
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In this paper,a detailed analysis on the clock of STM32 microcontroller based on the ARM Cortex nuclear is given.Through this paper you can have a basic understanding on the clock of STM32 microcontroller in order to further study and use the STM32 microcontroller.
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Digital clock manager
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The article was devoted to the development of method for working with MPU-6050 sensor on I2C data bus, which will connect additional sensors through the use of free microcontroller contacts to stabilize the UAV flight. During the verification of the developed method, the results of data exchange between STM32 microcontroller and GY-521 module were obtained using alternative contacts of the microcontroller instead of traditional ones. Figs.: 4. Tabl.: 1. Refs.: 13 titles.Keywords: method; sensor; data bus; microcontroller; contact; data exchange.
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Data Exchange
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We investigate automatic geolocation (i.e. identification of the location, expressed as latitude/longitude coordinates) of documents. Geolocation can be an effective means of summarizing large document collections and it is an important component of geographic information retrieval. We describe several simple supervised methods for document geolocation using only the document's raw text as evidence. All of our methods predict locations in the context of geodesic grids of varying degrees of resolution. We evaluate the methods on geotagged Wikipedia articles and Twitter feeds. For Wikipedia, our best method obtains a median prediction error of just 11.8 kilometers. Twitter geolocation is more challenging: we obtain a median error of 479 km, an improvement on previous results for the dataset.
Geolocation
Geographic coordinate system
Longitude
Geotagging
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The novel coronavirus disease (Covid-19) is a global problem that has caused many changes in people's lives. One of the problems is distance education, that has caused a difficulty form of study. Students often do not have required study components, because they are in the home and teacher does not have complete control over them. This paper described remote control and monitor system for the microcontroller technique subject, where the teacher gets possibilities for monitoring each student's microcontroller program. The subject is focused to the basic peripherals and functionalities of STM32 microcontrollers and internet communication based on the ESP8266 chip. Therefore, the article contains of monitoring module design, remote control application and simple test of the remote-control scanner for STM32 microcontrollers focused to the distance form of study.
STM32
Remote Control
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Geolocation
Geographic coordinate system
Longitude
Location-based service
Georeference
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Many users use a location-based application on a portable device to be a navigator when driving. However, there exists an incident that two roads are located on the same geolocation, i.e., same values of latitude and longitude but different altitude, for very long distance where one road is located on the ground level and another one is elevated. This incident mostly confuses a location-based application to precisely retrieve the actual road that a vehicle is currently on and, consequently, causes the application to either navigate incorrectly or suggest a route that is a detour. Calling an altitude from a GPS sensor might be a possible solution but it came with problems of accuracy, especially for mid-grade GPS sensors that equipped with most smartphone in today’s market. We proposed a concept of implementing a classification model that can classify whether a vehicle is on a ground road or an elevated road regardless of geolocation data. We trained and validated two models using a dataset that we had collected from actual driving on two roads in Thailand that fell under this condition. A data instance that we collected contained measurements related to driving or driving environment such as a real-time speed at any certain interval of time. We reported validation results of both models as well as other important statistics.
Geolocation
Geographic coordinate system
Longitude
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