Machine-to-Machine (M2M) collaboration opens new opportunities where systems can collaborate without any human intervention and solve engineering problems efficiently and effectively. M2M is widely used for various ap...Machine-to-Machine (M2M) collaboration opens new opportunities where systems can collaborate without any human intervention and solve engineering problems efficiently and effectively. M2M is widely used for various application areas. Through this reported project authors developed a M2M system where a drone and two ground vehicles collaborate through a base station to implement a system that can be utilized for an indoor search and rescue operation. The model training for drone flight paths achieves almost 100% accuracy. It was also observed that the accuracy of the model increased with more training samples. Both the drone flight path and ground vehicle navigation are controlled from the base station. Machine learning is utilized for modelling of drone’s flight path as well as for ground vehicle navigation through obstacles. The developed system was implemented on a field trial within a corridor of a building, and it was demonstrated successfully.展开更多
The paper describes the development of a text reader for people with vision impairments. The system is designed to extract the content of written documents or commercially printed materials. In terms of hardware, it u...The paper describes the development of a text reader for people with vision impairments. The system is designed to extract the content of written documents or commercially printed materials. In terms of hardware, it utilizes a camera, a small embedded processor board, and an Alexa Echo Dot. The software involves an open source text detection library called Tesseract along with Leptonica and OpenCV. The system in its current version can only work with English text. By using the Amazon cloud web services, a skill set was deployed, which would read aloud the detected text utilizing a OpenCV program via the Alexa Echo Dot. For this development, a Raspberry Pi was utilized as the embedded processor system.展开更多
The paper presents a web based vision system using a networked IP camera for tracking objects of interest. Three critical issues are addressed in this paper. First is the detection of moving objects in the foreground;...The paper presents a web based vision system using a networked IP camera for tracking objects of interest. Three critical issues are addressed in this paper. First is the detection of moving objects in the foreground;second is the control of pan-tilt-zoom (PTZ) IP cameras based on object location;and third is the collaboration of multiple cameras over the network to track objects of interests independently. The developed system utilized a network of PTZ cameras along with a number of software tools for this implementation. The system was able to track a single and multiple objects successfully. The difficulties in the detection of moving objects are also analyzed while multiple cameras are collaborating over a network utilizing PTZ cameras.展开更多
文摘Machine-to-Machine (M2M) collaboration opens new opportunities where systems can collaborate without any human intervention and solve engineering problems efficiently and effectively. M2M is widely used for various application areas. Through this reported project authors developed a M2M system where a drone and two ground vehicles collaborate through a base station to implement a system that can be utilized for an indoor search and rescue operation. The model training for drone flight paths achieves almost 100% accuracy. It was also observed that the accuracy of the model increased with more training samples. Both the drone flight path and ground vehicle navigation are controlled from the base station. Machine learning is utilized for modelling of drone’s flight path as well as for ground vehicle navigation through obstacles. The developed system was implemented on a field trial within a corridor of a building, and it was demonstrated successfully.
文摘The paper describes the development of a text reader for people with vision impairments. The system is designed to extract the content of written documents or commercially printed materials. In terms of hardware, it utilizes a camera, a small embedded processor board, and an Alexa Echo Dot. The software involves an open source text detection library called Tesseract along with Leptonica and OpenCV. The system in its current version can only work with English text. By using the Amazon cloud web services, a skill set was deployed, which would read aloud the detected text utilizing a OpenCV program via the Alexa Echo Dot. For this development, a Raspberry Pi was utilized as the embedded processor system.
文摘The paper presents a web based vision system using a networked IP camera for tracking objects of interest. Three critical issues are addressed in this paper. First is the detection of moving objects in the foreground;second is the control of pan-tilt-zoom (PTZ) IP cameras based on object location;and third is the collaboration of multiple cameras over the network to track objects of interests independently. The developed system utilized a network of PTZ cameras along with a number of software tools for this implementation. The system was able to track a single and multiple objects successfully. The difficulties in the detection of moving objects are also analyzed while multiple cameras are collaborating over a network utilizing PTZ cameras.
