We have developed a wide frequency range affordable optical chopper system from 10-550 Hz. It is a self-contained prototype built using 3D design and printing and arduino uno. The system consists of six chopper wheels...
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Automation the process of monitoring the garden can transform garden irrigation process from being manual and static to smart and dynamic one. This leads to higher comfortability, water using efficiency and less human...
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ISBN:
(纸本)9781510881679
Automation the process of monitoring the garden can transform garden irrigation process from being manual and static to smart and dynamic one. This leads to higher comfortability, water using efficiency and less human supervision effort. This paper proposes a cloud based Internet of Things (IoT) smart garden monitoring and irrigation system using arduino uno. The watering requirement for a plant can be adjusted by monitoring the soil moisture. Measuring the soil moisture of the plant gives information if the plant is ideally watered, over watered or under watered. The proposed system monitors and maintains two quantities of the garden, the garden soil moisture content and light intensity. This is done using soil moisture sensors and light intensity sensor. The monitored data is sent continuously to ThinkSpeak IoT cloud. In the cloud the data gathered from the system is analyzed and when a target threshold of soil moister is reached, an action is sent accordingly from the cloud to the garden automatic watering system to irrigate the garden. arduino uno microcontroller is used to implement the system control unit. IoT is used to keep the garden owner updated about the status of the sprinklers. Information from the sensors is regularly updated on a ThinSpeack IoT cloud and the user can check the water sprinklers status at any time. In addition, the sensor readings are transmitted to a ThingSpeak channel to generate graphs for analysis.
IoT is essential in today's surveillance environment for maintaining safety and providing the best fire detection performance. Cameras are being installed in a lot of places because fire can seriously damage both ...
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IoT is essential in today's surveillance environment for maintaining safety and providing the best fire detection performance. Cameras are being installed in a lot of places because fire can seriously damage both residential and commercial sectors. However, the installed video monitoring device may generate data or perspectives that are odd or skewed. In view of these shortcomings, a convolutional neural network-based approach is proposed. The data set for testing the model is provided by an integrated sensor system that was built using an ESP-32 CAM image sensor, a number of complementing sensors, and an arduino uno microcontroller. Using drop out techniques, the model also solves the issue of overfitting in the paper. The performance of our approach was compared to that of other transfer learning models, such as MobileNet, Resnet50 and VGG19 that uses well-known state-of-the-art architectures. The main goal of this paper is to build a model which gives high accuracy while consuming low computational power during inference. The proposed model accuracy relative to latency is better than the transfer learning models. Furthermore, the approach is to build a well-generalised model for unknown data, resulting in efficient generalisation and fewer false predictions.
The population is increasing on this growing planet, and as a result, security issues are developing as well. In this situation, safety is one of the major concerns. It might not be able to physically secure everyone ...
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The population is increasing on this growing planet, and as a result, security issues are developing as well. In this situation, safety is one of the major concerns. It might not be able to physically secure everyone due to the large population. Currently, CCTV cameras are used for security, but they are costly and can't be installed everywhere. Internet of Things (IoT) became a possibility as a result. Therefore, we suggest a security patrolling robot for public protection that can substitute personnel and deliver high-quality security. In this system, a Raspberry Pi, camera, sound sensors, servo motor, and Global Positioning System (GPS) Module are all mounted on the robotic vehicle. This camera, mounted on a servo motor, is utilized for live streaming and recording live events. The robotic vehicle displays the live event and moves the camera 45 degrees to the right & left if it detects any sound. GPS module is used to track the bot's location. Therefore, we are developing a bot that can be deployed to secure a broad region.
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