object detection model

Air pollution is the biggest environmental hazard that cannot be ignored. Due to increase in number of industries and urbanization increases air pollutants concentrations in many areas because of this different changes are been happening in human life like health issues and as well as other living organisms. We have some pollutant emission monitoring systems, like Opsis, Codel, Urac and TAS-Air metrics which are expensive. As well as these systems have limitations to be installed on chimney due to their principle of operation. In this work I like to propose a function that is easy to use and causes less cost compared to the other ones. That is an industrial air pollution monitoring system based on the technology of Wireless Sensor Networks (WSNs). This system is integrated with the Global System for Mobile (GSM) communications and the protocol it uses is zigbee. The system consists of sensor nodes, a control center and data base through which sensing data can be stored for history and future plans. It is used to monitor Carbon Monoxide (CO), Sulfur Dioxide (SO2) and dust concentration caused by industrial emissions due to process.

Household object detection is a brand-new computer technique that combines image processing and computer vision to recognize objects in the home. All objects stored in the kitchen, room, and other areas will be detected by the camera. Low-end device techniques for detecting people in video or images are known as object detection. With picture and video analysis, we've lost our way.

We all know forest is very important resource of oxygen. Saving our environmental resources is human beings responsibility. One of the techniques to save forests is forest fire detection. This is a technique used to detect the fire and prevent them in less time. Forest fire leads to death of wild life and trees. There are other techniques used to detect fire in forests like cameras, satellite system, manual monitoring but they take time to detect the fire whereas Forest fire detection system detects the fire within seconds and triggers the alarms. In this way we can save tress and wildlife in very less time.

Wireless sensor network technologies normally deploy a large number of small, low cost sensors, fairly densely that can observe and influence the physical world around them by gathering physical information, transform it into electrical signals, send it to a remote location to do some analysis and deploy the results in different applications. This means there is no need to build towers or set up complicated communication links such as; microwave and satellite. It can be deployed anywhere, even in inaccessible places. This technology can provide a real time monitoring for forest fire, where it can provide information at the ignition instance or at very small delay, depends on the node used wake up/sleep schedule. It’s more reliable because it can influence the world in the surrounded area, if it is used in appropriate methods, rather than expecting events over large distances and long delay like other satellite and camera towers techniques. In this work, all nodes only use temperature sensors and they are programmed on a certain threshold temperature, above it the node will send an alarm message to the sink. This concept relies solely on the node behavior to alert of crises possibility using simple node components to provide detection and information on whether this is a peaceful fire, or the beginning of wild fire. The key in this method is to make decisions by tracking the fire propagation and check the logic behind it.

Parking and transportation becoming crucial from decades, the accidents per day around the world are increasing, so with sensors we can drastically decrease the death rate and accident rate around the world. In this paper I suppose to present you the sensors-based cloud smart parking and sensors-based AI and ML smart transportation.

Household object detection is a brand-new computer technique that combines image processing and computer vision to recognise objects in the home. All objects stored in the kitchen, room, and other areas will be detected by the camera. Low-end device techniques for detecting people in video or images are known as object detection. With picture and video analysis, we've lost our way.