In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals o...

Wireless communication technologies are pervasive in today’s everyday environment. Together with the ever-dropping cost for equipment relying on such technology, this abundance gives rise to a wealth of applications well beyond communication itself. Utilizing communication technologies in the context of mobile sensing seems to be an especially promising approach, as mobile phones and other pers...

Mobile embedded systems increasingly use transactions for applications like mobile inventory, mobile commerce or commercial applications. Yet, many issues are challenging and need to be resolved before enabling mobile devices to take part in distributed computing. Mobile environment limitations make it harder to design appropriate and efficient commit protocols. There are a handful of protocols...

This thesis is aimed at evaluating the suitability of agile methods for mobile application development projects, bringing a set of improvements to an established agile method called Mobile-D, and providing tool support to enable these improvements, facilitating performance testing and usage logging in the lifecycle. The motivation for this work is to better understand mobile development, and to...

Infrastructure less nature distinguish the Ad-hoc network from other networks. In Ad-hoc environment mobile nodes having wireless capability collaborate with each other to form a network. For this collaboration purpose each mobile node can act as router. Mobile nodes in Ad-hoc network can move around and are free to do so. By applying the restrictions caused by the infrastructure less, collabor...

One of the major scientific undertakings over the past few years has been exploring the interaction between humans and machines in mobile environments. We have smart devices with high computational power. Some devices are also aware of context. For example, some mobile devices have built in GPS, light sensor and other detection devices like [1]. In this work, we will examine how mobile device c...

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals o...

The better the technology, the more user friendly it becomes. This is what 4G brings to us than 3G. 4G provides us 3 times faster speed than 3G technology.4G is the short name of fourth generation of wireless /mobile communication That will enable things like IP –based voice, data, gamming services & high quality streamed multimedia on portable devices with cable modem like transmission speed. ...

Basic approaches of mobile cyber-physical systems (CPS) such like cars, trains, aeroplanes or spaceships are parts of our daily life. Mobile CPSs are embedded into a physical environment which is usually harsh and uncertain. Monitoring mobile CPSs is essential to ensure reliability and to avoid damage. Monitoring mobile CPSs presupposes knowledge about the CPS, the physical environment and the ...

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals o...