Turn On Light Raspberry Pi To Reduce Traffic Jam

Internet of Things (IoT) plays a pivotal part in our mundane daily life by controlling electronic devices using networks. The controlling is done by minutely observing the important parameters which generate vital pieces of information concerning the functioning of these electronic devices. Simultaneously, this information will transmit these vital statistics from the transmitting device as well as save the same on the cloud to access by the applications and supplementary procedures to use them. This scrutiny associates the outcomes of the environmental observances like the humidity and temperature measurements using sensors. The gathered information could be profitably used to produce actions like distantly dominant cooling, heating devices, or long term statistics, which will be useful to control the same. The detected data are uploaded to the cloud storage through network and associate using android application. The system employs Arduino UNO with Raspberry Pi, HTU 211D sensor device, and an ESP8266 Wi-Fi module. The experimental results show the live temperature and humidity of the surroundings and the soil moisture of any plant using Arduino UNO with Raspberry Pi. Raspberry Pi is mainly used here for checking the temperature and humidity through the HTU 211D sensor element. The sensors are used for measuring the temperatures from the surroundings, storing displayed information with different devices. Here, the ESP8266 Wi-Fi module has been used for data storing purpose.

Research Article| March 01, 2016 The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation Frank Sepulveda; Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Jay Pulliam Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Frank Sepulveda aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Jay Pulliam aDepartment of Geology, Baylor University, One Bear Place #97354, Waco, Texas 76798 U.S.A.frank_sepulveda@baylor.edu Publisher: Seismological Society of America First Online: 14 Jul 2017 Online Issn: 1938-2057 Print Issn: 0895-0695 © 2016 by the Seismological Society of America Seismological Research Letters (2016) 87 (2A): 345–357. https://doi.org/10.1785/0220150234 Article history First Online: 14 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Frank Sepulveda, Jay Pulliam; The Internet of Geophysical Things: Raspberry Pi Enhanced REF TEK (RaPiER) System Integration and Evaluation. Seismological Research Letters 2016;; 87 (2A): 345–357. doi: https://doi.org/10.1785/0220150234 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietySeismological Research Letters Search Advanced Search ABSTRACT The proliferation of commercial Internet of Things (IoT) devices is raising consumers’ awareness of the benefits of enhancing everyday objects with the ability to communicate, sense, and process information. Commercial‐off‐the‐shelf (COTS) versions of the embedded technologies responsible for the rise of the IoT are easy‐to‐use, inexpensive, and relatively powerful. IoT Makers, technological do‐it‐yourself enthusiasts, utilize these technologies and the IoT ecosystem to create IoT devices that range from casual hobbyist to entrepreneurial in nature.In an effort to develop a “no‐engineer‐needed” Internet of Geophysical Things (IoGT) device, we integrated a COTS embedded computer with a geoscience‐related COTS data acquisition system (DAS). Using skills common to geoscientists, we integrated the Raspberry Pi System‐On‐Chip with the REF TEK (a Trimble brand) 130‐01 DAS. This Raspberry Pi enhanced REF TEK (RaPiER) provides IoGT Makers a platform for the development of geoscientific sensor node or network enhancements. IoGT Makers can use the RaPiER to tinker with IoT capabilities while simultaneously acquiring research‐quality data. Geoscientific (i.e., seismic) application areas that may benefit from RaPiER, particularly RaPiER nodal processing, include earthquake and engineering seismology.In this article, we discuss the emerging technologies that allow IoGT Makers to build their own IoGT device. We review our selection of the Raspberry Pi and REF TEK 130‐01 for IoGT device integration. We provide a RaPiER system integration guide and REF TEK interface software compiled for the Raspberry Pi ( available in the electronic supplement to this article). We present methods to expand RaPiER capabilities using the Raspberry Pi’s ecosystem. Last, we discuss our evaluation of RaPiER’s performance and its suitability for realistic field deployments. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.

Various of environmental applications has implemented IoT technology as a solution in solving problems. For instance, air quality measurements. There are many communication technologies used to measure air quality by utilizing Wireless Sensor Network (WSN), Wi-Fi, Bluetooth, and LoRa as communication medias. This study aims to implement the Message Queuing Telemetry Transport (MQTT) protocol in monitoring environmental conditions. MQTT is implemented using the ESP8266 Wi-Fi module, temperature sensor, humidity sensor, and Carbon Dioxide (CO2) sensor. Furthermore, the modules will send data to the MQTT broker using a wireless network which running on the Raspberry Pi. As a result, there is no packet loss when using the MQTT protocol. All environmental data can be monitored in real time using web-based application.

This paper presents the design of an IoT based air pollution monitoring system to measure carbon dioxide gas, butane gas, humidity and temperature. The hardware consists of MQ-2 gas sensor, ESP8266 Wi-Fi module, DHT22 temperature and humidity sensors. Meanwhile, the software used in this prototype is the Arduino Integrated Development Environment (IDE) written in function C and C++. The monitoring system indicate air quality is below than 100 AQI for safety air quality and more than 200 AQI for hazardous air quality. The green LED illuminated indicates there is no hazardous gas detected. Meantime, when the butane gas or carbon dioxide gas is identified, the red LED is illuminated. All the data are sent through ThingSpeak and Blynk applications. In ThingSpeak and Blynk applications, the data are displayed and updated after detected by the sensors in every 15 seconds and 1 second. In the Blynk application, when the hazardous gas is detected, the Blynk application sends a notification to alert the users immediately.

The Internet of Things (IoT) is defined by the interconnection between networks of smart devices (objects) through specific communication standards and protocols. Data retrieved from these objects is loaded on cloud servers where it is analyzed, processed and then accessed by users through simple, intuitive, easy-to-use interfaces. The rapid development of IoT applications will steadily increase the demand for skilled personnel in this field. Under these circumstances, the study of IoT basic notions in classrooms becomes a necessity. Using the Arduino and Raspberry Pi development platforms, a wide range of IoT projects can be developed, according to the students' level. These platforms capture environmental data through an extended array of sensors (temperature, light, pressure, humidity, force, acceleration, rotation, sound, IR, magnetic field, etc.), making it perfectly suited to projects development in the educational STEM field (Science, Technology, Engineering and Matemathics). In this study my aim is to show, based on examples, how several IoT projects can be developed in class using the two above mentioned platforms and I emphasize the didactical aspects associated with this study. For the first project I used the Arduino Uno development board, the DHT11 temperature and humidity sensor, and ESP8266 WiFi module, and showed how the ambient temperature and humidity can be monitored via Internet. The data collected by the sensor was processed by Arduino, sent to the WiFi module and further on a cloud server on the IoT ThingSpeak platform where it was stored, analyzed and graphically represented in real time. In the second project I used a Raspberry Pi development board, a mobile robotic platform powered by two electric motors and equipped with a webcam in order to video monitor, via the Internet, a particular perimeter under observation. The robotic platform on which the surveillance camera is located can be positional controlled using a web browser that can access an HTML page built for this purpose. The final part of this study is dedicated to the assessment of the quality of STEM training results by classes of students who have worked on IoT projects compared with classes that have undergone traditional training courses.

This project presents the Smart Voice User Interface (VUI) Office Monitoring System that interacts with the Internet of Things (IoT) to complete task based on user’s commands. In order to reduce the spread of Covid-19, touchless switches are vital to be used in practice. The Raspberry Pi is used as a microcontroller in this VUI system with Phyton programming language. The electrical components used, such as LED lights and air conditioners, are connected through the General-Purpose Input Output (GPIO) of Raspberry Pi and relay module. The air conditioner is represented with a fan using a motor while lights using LED lights. The outputs can be controlled by giving commands to the Google Assistant or using the Blynk application that relates to the virtual assistant. The interface of the Blynk application shows buttons as an indicator for turning the lights and air conditioner ON or OFF. An application called If This Then That (IFTTT) is used to trigger the GPIO pins based on the instruction commands made in the Blynk application and Google Assistant. A pair of microphones and speakers are also connected with the Raspberry Pi as input and output voice commands. The outcome of the propose technique is a system which controls the devices using voice recognition and artificial intelligence that result in reducing the spread of covid-19 in an office environment. This will be beneficial for office staff for daily scheduled use and personal usage. As a conclusion, this system is efficient and suitable to be used during this pandemic because it eliminates the need to touch various surfaces in office environment.

Koi fish is one type of ornamental fish that is much loved because it has a beautiful shape, color, and pattern. Quality koi fish can be formed with a good maintenance pattern and do not rule out environmental factors and feed, especially when koi fish are still seed-sized and maintained in aquariums when feeding and controlling the state of water temperature should be done regularly. This research aims to create an intelligent fish farm system in the form of feeding and monitoring water temperature based on the internet of things that can be controlled through a smartphone in the Blynk application as an automation system that can increase efficiency in koi fish cultivation. In this prototype, the feeding process uses the HX711 Load Cell module, RTC DS3231 sensor, and DS18B20 sensor for water temperature monitoring controlled using Atmega 2560 Arduino microcontroller with connection access using ESP8266 WiFi module, which is then delivered to Blynk application. Feeding is carried out based on the time and weight of the feed that has been determined. In the temperature control system, if the temperature is less than 25°C, then the lamp will turn on, and if the temperature is more than 27°C, then the fan will turn on, and if the temperature ranges from 25-27°C, then the fan and lights are off. The result of this study is that it can monitor the feeding process and the temperature of aquarium water in koi fish cultivation automatically.

Internet of Things (IoT) based Advanced cardiac Arrest Detection system have an expansive potential of becoming an integral part of the future medical system. In particular, these systems can play life-saving roles for monitoring of patients with critical health issues. Any health care monitoring system must be free from incorrect data, which may arise because of instrument failure or communication errors. In this project, to detect reliability and accuracy of data obtained by the IoT-based remote health monitoring. This project makes a use of MAX30100 (heartbeat & oxygen), ESP8266 Wi-Fi module and Arduino nano. The main controlling device of the project is Arduino nano microcontroller. Arduino will continuously read the heartbeat and spo2 value through MAX30100 sensor and will be sent to the blynk mobile application through esp8266 Wi-Fi module. User can access this device using smart mobile from anywhere in the world. To achieve this task microcontroller loaded program written in embedded C language.

The intelligent access control system designed in this article can be unlocked through three modes: fingerprint, IC card, and digital password. It will automatically lock after multiple incorrect password inputs, and can establish a connection with the mobile phone APP via WiFi, allowing users to remotely control or monitor the door locks at home. In the hardware part, this system uses the STM32F103C8T6 single-chip microcontroller as the main controller, and the ESP8266-WiFi module as the communication module. Various sensors and actuators are combined to build a complete system. In the unlocking mode, the intelligent access control system reads the fingerprint, IC card, and password data in real time, processes and compares them with the single-chip microcontroller, and confirms whether to unlock. It then coordinates the servo module to complete the unlocking process. In the administrator mode, users can freely add or delete unlocking data. The display screen will show the various options in both modes in real time, facilitating operation, and display the unlocking status in real time. The system completes communication with the mobile phone through the ESP8266-WiFi module, allowing users to set passwords remotely and control the opening and closing of the door lock via the mobile phone. When a certain unlocking mode fails to be verified for three consecutive times, the system will give an alarm, and that particular unlocking method will be locked. Users can unlock by trying other unlocking methods.

not spread evenly among the people. Most people still use traditional methods and depend on the uncertain climate to meet their food needs, such as vegetables and fruits. Based on this, an Internet of Things (IoT) based Smart Greenhouse Design with Arduino Uno Microcontroller was created as a solution that is expected to help make it easier for farmers to cultivate plants. The greenhouse is a building that has the function to protect plants from external disturbances such as pests, heavy rain, strong winds, and excessive humidity. Meanwhile, what is called a smart greenhouse that uses technology such as the Internet of Things (IoT), is designed to automatically monitoring uses the Arduino Uno microcontroller as the control center for each sensor used, namely DHT22 (air temperature and humidity sensor), Soil Moisture (soil moisture sensor), GUVA-S12SD (UV light intensity sensor). The sensor will obtain the required data and will be automatically sent to the server (blynk application) with the help of ESP8266 (wifi module). The method used in this study is engineering design in the manufacture of the automation system. The results of this research are in the form of a smart greenhouse that can regulate, adjust, and modify the climate to optimize the conditions and processes of plant growth in the greenhouse equipment through microcontrollers and monitoring devices such as sensors and can be controlled remotely via mobile phones or computers everywhere.

The upcoming technological era 5G has increased the interest towards IOT significantly, the ability of IOT (Internet of Things) which is able to render and connect multiple IOT devices and its services from any location through various applications makes the use of this technology more efficient towards its future enterprise. The introduction of smart IOT technologies which is the present stream of automation in cars has allowed the devices to connect and communicate from any location. In an overpopulated nation like India finding a parking space for a car is a major concern especially in a metropolitan city, searching for a car parking space may sometimes result in traffic or wrong parkings might lead to penalties and traffic. Here an online booking system of networking devices based on IOT-cloud platform from where the user can get the information of parking slots empty or full in the area of choice and the user can get the information of the number of empty slots in that particular place and can book a parking slot in advance. The system of the model is presented in such a way that car parking update can be done offline without any booking and the update of the car parked at the slot is shown on the website in real time. The proposed project is implemented using 2G GSM SIM800A module with ESP8266 Wi-Fi module, we have used ThingSpeak open -source software for the IOT platform cloud database service through which an end user can use it to check the availability of the parking slot and book it accordingly.Here a systematic car parking sytem model is presented

This research discusses the design and build of an Internet of Things (IoT)-based vending machine prototype with a payment method using Radio Frequency Identification (RFID). The system is designed using the ESP32 microcontroller connected to an RFID reader, DC motor, photointerrupter sensor, and RTC as the main controller. The Blynk application is used as a medium for monitoring drink stock and real-time notifications. Test results show that the prototype can perform cashless transactions with RFID automatically, dispense products according to user selection, and display stock data through the Blynk application. The application of RFID and IoT technology in vending machines has proven to improve operational efficiency, reduce cash transaction usage, and provide a more practical transaction experience. This research is expected to be a modern solution for digitally based automatic sales systems in the future.

In recent days modern environment industries are facing rapid flourishing for performance capabilities and their requirements for corporate clients and industrial sector. Internet of Things (IoT) is an innovative and rapidly growing field for automation and evaluation in networks, Artificial Intelligence, data sensing, data mining, and big data. These systems have a great tendency to monitor and control different process used in industries. IoT systems have been implemented and have applications in different industries due to their cost-effectiveness and flexibility In this paper we have developed a system which includes real-time monitoring of current reading of three-phase motor through a wireless network. With the help of this system, data can be saved and monitored and then transmitted to cloud storage. This system contains Arduino-UNO board, ACS-712 current sensor, ESP-8266 Wi-Fi module which sends information to an IoT API service THING-SPEAK that behave like a cloud for various sensors to monitor data. The proposed system was successfully deployed in Aisha Steel Mills, Karachi, Pakistan.

Current attendance methods, though simple, are prone to manipulation and can be time consuming for both educators and students. For instance, manual systems and QR code based methods allow students to register attendance on behalf of others due to the lack of unique identification. While calling names individually improves security, it disrupts the learning process by consuming significant time. This study addresses these issues by developing an autonomous robot, CObot, equipped with a facial recognition system powered by a Raspberry Pi microcontroller. CObot navigates classrooms autonomously, avoiding obstacles, and efficiently records attendance without requiring movement from students or educators. The use of facial recognition ensures that only registered individuals can mark attendance, creating a secure and tamper-proof system. Additionally, the integration of Internet of Things (IoT) technology enables real-time data transfer to Google Sheets, simplifying record-keeping and reducing educators administrative workload. A 3D-printed, customizable car structure enhances the robot design, while the Raspberry Pi 5 was selected over alternatives like the ESP32-S3 for its superior processing power and faster data transfer speeds, ensuring smoother operations. In testing with 60 participants, the Raspberry Pi 5 demonstrated a 99% accuracy rate in facial recognition, outperforming the ESP32-S3 90% accuracy. By saving time, improving security, and reducing manual effort, CObot enhances the classroom environment, benefiting both students and educators. While the improvement in attendance systems may appear incremental, CObot represents a meaningful step toward fostering a more efficient and effective learning environment.

HRS Expert Consensus Statement on remote interrogation and monitoring for cardiovascular implantable electronic devices.