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Time series modeling is a commonly used approach in exchange for studying and analyzing the data to support decision-making in companies based on historical data and thereby help them to save costs. This work introduces a forecasting framework that utilizes a seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model to forecast the number of people expected to enter a building within a short period. We applied the model to forecast the abovementioned value at California University Irvine's main door using an open-source dataset that comprised data spanning four months. The experimental results demonstrate that the SARIMAX model exhibits encouraging performance in classification andevaluation, as evidenced by the promising results. The RMSE values for one,two, three, and four prediction weeks are 24.6, 40.4, 36, and 38.7, respectively, accompanied by corresponding percentage errors of 2%, 4.8%,4.76%, and 1.01%. These metrics highlight the model's ability to predict outcomes accurately and indicate its effectiveness in forecasting over various time horizons. Furthermore, the proposed model addresses the issue of inadequate future planning and analyzes foot traffic to provide a reliable forecasting technique, which is essential for modern building facilities management.

Time series modeling is a commonly used approach in exchange for studying and analyzing the data to support decision-making in companies based on historical data and thereby help them to save costs. This work introduces a forecasting framework that utilizes a seasonal autoregressive integrated moving average with exogenous variables (SARIMAX) model to forecast the number of people expected to enter a building within a short period. We applied the model to forecast the abovementioned value at California University Irvine's main door using an open-source dataset that comprised data spanning four months. The experimental results demonstrate that the SARIMAX model exhibits encouraging performance in classification andevaluation, as evidenced by the promising results. The RMSE values for one,two, three, and four prediction weeks are 24.6, 40.4, 36, and 38.7, respectively, accompanied by corresponding percentage errors of 2%, 4.8%,4.76%, and 1.01%. These metrics highlight the model's ability to predict outcomes accurately and indicate its effectiveness in forecasting over various time horizons. Furthermore, the proposed model addresses the issue of inadequate future planning and analyzes foot traffic to provide a reliable forecasting technique, which is essential for modern building facilities management.

Real-time people counting is a beneficial system that covers many levels of use cases. It can help keep track of the number of people entering buildings, buses, stores, and other facilities. Knowing such information can be helpful in case of fire emergencies, preventing overcrowding in public transportation and facilities, helping people with social anxiety, and more. The use cases of such a device are endless and can significantly help society’s development. This thesis will provide research and a solution for accurate real-time people counting using two devices. Having multiple devices count the number of people passing through with good accuracy would benefit facilities with multiple exits. Two Coral Dev Boards will be used, each with its web camera. With the help of machine learning, the device will recognize the top of the head of people passing through and count them, which will later be sent to a server that counts the total amount from each device. The results varied between66.7 % and 100 % accuracy, depending on the walking speed. A fast-paced walking speed, almost running, resulted in 66.7 % accuracy. Meanwhile, a regular walking speed resulted in 80-100 % accuracy.

Real-time people counting is a beneficial system that covers many levels of use cases. It can help keep track of the number of people entering buildings, buses, stores, and other facilities. Knowing such information can be helpful in case of fire emergencies, preventing overcrowding in public transportation and facilities, helping people with social anxiety, and more. The use cases of such a device are endless and can significantly help society’s development. This thesis will provide research and a solution for accurate real-time people counting using two devices. Having multiple devices count the number of people passing through with good accuracy would benefit facilities with multiple exits. Two Coral Dev Boards will be used, each with its web camera. With the help of machine learning, the device will recognize the top of the head of people passing through and count them, which will later be sent to a server that counts the total amount from each device. The results varied between66.7 % and 100 % accuracy, depending on the walking speed. A fast-paced walking speed, almost running, resulted in 66.7 % accuracy. Meanwhile, a regular walking speed resulted in 80-100 % accuracy.

[ES] Se desarrolla un dispositivo sensor inalámbrico, capaz de detectar la dirección y sentido del tráfico en la entrada de una instalación, almacenando y enviando los parámetros recolectados mediante el uso de una red LPWAN. Posteriormente estos parámetros podrán ser tratados y analizados mediante una interfaz de usuario, y poder prevenir un aforo superior al recomendado., [EN] A wireless sensor device is developed, capable of detecting the direction and way of traffic at the entrance of a facility, storing and sending the collected parameters through the use of an LPWAN network. Later on, these parameters can be treated and analysed through a user interface, to prevent a number higher than recommended., [CA] Es desenvolupa un dispositiu sensor sense fils, capaç de detectar la direcció i sentit del trànsit en l'entrada d'una instal·lació, emmagatzemant i enviant els paràmetres recol·lectats mitjançant l'ús d'una xarxa LPWAN. Posteriorment aquests paràmetres podran ser tractats i analitzats mitjançant una interfície d'usuari, i poder previndre un aforament superior al recomanat. En concret, s'estudien les diferents tecnologies de comunicació sense fils de baix cost, entrant detalladament de les característiques i la composició d'aquestes xarxes, per a poder determinar la mes indicada per al desenvolupament del projecte. A més, es dissenya la xarxa i l'aplicació web, per a visualitzar les dades de manera efectiva i pràctica.

[ES] Se desarrolla un dispositivo sensor inalámbrico, capaz de detectar la dirección y sentido del tráfico en la entrada de una instalación, almacenando y enviando los parámetros recolectados mediante el uso de una red LPWAN. Posteriormente estos parámetros podrán ser tratados y analizados mediante una interfaz de usuario, y poder prevenir un aforo superior al recomendado., [EN] A wireless sensor device is developed, capable of detecting the direction and way of traffic at the entrance of a facility, storing and sending the collected parameters through the use of an LPWAN network. Later on, these parameters can be treated and analysed through a user interface, to prevent a number higher than recommended., [CA] Es desenvolupa un dispositiu sensor sense fils, capaç de detectar la direcció i sentit del trànsit en l'entrada d'una instal·lació, emmagatzemant i enviant els paràmetres recol·lectats mitjançant l'ús d'una xarxa LPWAN. Posteriorment aquests paràmetres podran ser tractats i analitzats mitjançant una interfície d'usuari, i poder previndre un aforament superior al recomanat. En concret, s'estudien les diferents tecnologies de comunicació sense fils de baix cost, entrant detalladament de les característiques i la composició d'aquestes xarxes, per a poder determinar la mes indicada per al desenvolupament del projecte. A més, es dissenya la xarxa i l'aplicació web, per a visualitzar les dades de manera efectiva i pràctica.

[ES] Se desarrolla un dispositivo sensor inalámbrico, capaz de detectar la dirección y sentido del tráfico en la entrada de una instalación, almacenando y enviando los parámetros recolectados mediante el uso de una red LPWAN. Posteriormente estos parámetros podrán ser tratados y analizados mediante una interfaz de usuario, y poder prevenir un aforo superior al recomendado., [EN] A wireless sensor device is developed, capable of detecting the direction and way of traffic at the entrance of a facility, storing and sending the collected parameters through the use of an LPWAN network. Later on, these parameters can be treated and analysed through a user interface, to prevent a number higher than recommended., [CA] Es desenvolupa un dispositiu sensor sense fils, capaç de detectar la direcció i sentit del trànsit en l'entrada d'una instal·lació, emmagatzemant i enviant els paràmetres recol·lectats mitjançant l'ús d'una xarxa LPWAN. Posteriorment aquests paràmetres podran ser tractats i analitzats mitjançant una interfície d'usuari, i poder previndre un aforament superior al recomanat. En concret, s'estudien les diferents tecnologies de comunicació sense fils de baix cost, entrant detalladament de les característiques i la composició d'aquestes xarxes, per a poder determinar la mes indicada per al desenvolupament del projecte. A més, es dissenya la xarxa i l'aplicació web, per a visualitzar les dades de manera efectiva i pràctica.

El proyecto (PePiCo:People Pi Counter) tiene como propósito implementar un algoritmo capaz de determinar el número de personas que atraviesan una barrera virtual, distinguiendo el sentido de la marcha, para su ejecución sobre un dispositivo Raspberry Pi.

El proyecto (PePiCo:People Pi Counter) tiene como propósito implementar un algoritmo capaz de determinar el número de personas que atraviesan una barrera virtual, distinguiendo el sentido de la marcha, para su ejecución sobre un dispositivo Raspberry Pi.

El proyecto (PePiCo:People Pi Counter) tiene como propósito implementar un algoritmo capaz de determinar el número de personas que atraviesan una barrera virtual, distinguiendo el sentido de la marcha, para su ejecución sobre un dispositivo Raspberry Pi.

This paper presents the design principles underlying the video nodes of long-lifetime wireless networks. The hardware and firmware architectures of the system are described in detail, along with the system-power-consumption model. A prototype is introduced to validate the proposed approach. The system mounts a Flash-based field-programmable gate array and a high-dynamic-range complementary metal-oxide-semiconductor custom vision sensor. Accurate power measurements show that the overall consumption is 4.2 mW at 3.3 V in the worst case, thus achieving an improvement of two orders of magnitude with respect to video nodes for similar applications recently proposed in the literature. Powered with a 2200-mAh 3.3-V battery, the system will exhibit a typical lifetime of about three months. © 2011 IEEE.

This paper presents the design principles underlying the video nodes of long-lifetime wireless networks. The hardware and firmware architectures of the system are described in detail, along with the system-power-consumption model. A prototype is introduced to validate the proposed approach. The system mounts a Flash-based field-programmable gate array and a high-dynamic-range complementary metal-oxide-semiconductor custom vision sensor. Accurate power measurements show that the overall consumption is 4.2 mW at 3.3 V in the worst case, thus achieving an improvement of two orders of magnitude with respect to video nodes for similar applications recently proposed in the literature. Powered with a 2200-mAh 3.3-V battery, the system will exhibit a typical lifetime of about three months. © 2011 IEEE.