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An improved version of Alpha-N, a self-powered, wheel-driven Automated Delivery Robot (ADR), is presented in this study. Alpha-N-V2 is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. For autonomous navigation and path planning, Alpha-N uses a vector map and calculates the shortest path by Grid Count Method (GCM) of Dijkstra’s Algorithm. The RFID Reading System (RRS) is assembled in Alpha-N to read Landmark determination with Radio Frequency Identification (RFID) tags. With the help of the RFID tags, Alpha-N verifies the path for identification between source and destination and calibrates the current position. Along with the RRS, GCM, to detect and avoid obstacles, an Object Detection Module (ODM) is constructed by Faster R-CNN with VGGNet-16 architecture that builds and supports the Path Planning System (PPS). In the testing phase, the following results are acquired from the Alpha-N: ODM exhibits an accuracy of [Formula: see text], RRS shows [Formula: see text] accuracy and the PPS maintains the accuracy of [Formula: see text]. This proposed version of Alpha-N shows significant improvement in terms of performance and usability compared with the previous version of Alpha-N.

Fisherman of Bangladesh have little to no equipment on their boat to get help in time of need. Every year thousands of fishermen die on the sea because of natural disaster since they don't have any kind of system onboard which can transmit distress messages. A solution to this problem is to provide them an affordable system so that they can send distress alert to get help in their location. Hence to solve this problem this paper proposes a low-cost Solar powered GPS and GSM based boat distress alert system which can track boat location and during an emergency, it can send a distress message to rescue party with all necessary location information.

Alpha-N - A self-powered, wheel-driven Automated Delivery Robot (ADR) is presented in this paper. The ADR is capable of navigating autonomously by detecting and avoiding objects or obstacles in its path. It uses a vector map of the path and calculates the shortest path by Grid Count Method (GCM) of Dijkstra’s Algorithm. Landmark determination with Radio Frequency Identification (RFID) tags are placed in the path for identification and verification of source and destination, and also for the re-calibration of the current position. On the other hand, an Object Detection Module (ODM) is built by Faster R-CNN with VGGNet-16 architecture for supporting path planning by detecting and recognizing obstacles. The Path Planning System (PPS) is combined with the output of the GCM, the RFID Reading System (RRS) and also by the binary results of ODM. This PPS requires a minimum speed of 200 RPM and 75 s duration for the robot to successfully relocate its position by reading an RFID tag. In the result analysis phase, the ODM exhibits an accuracy of 83.75%, RRS shows 92.3% accuracy and the PPS maintains an accuracy of 85.3%. Stacking all these 3 modules, the ADR is built, tested and validated which shows significant improvement in terms of performance and usability comparing with other service robots.

Permanent Magnet Brushless DC (PMBLDC) motor has a huge scope of industrial application in modern automated industries. In this paper, an artificial neural network (ANN) based PMBLDC motor drives are proposed and the computational complexities of the neural network is avoided by using single neuron based neural network. Two types of neural network with different activation functions are considered in this paper. One is recurrent neural network (RNN) and another is feed forward back propagation (FFBP) based neural network. The performance of these proposed ANN based drives with respect to conventional adaptive PI controller is compared for different dynamic conditions. Considering starting characteristics there is no performance deviation among the proposed drives with respect to conventional drive system. But in case of dynamic speed changing condition, the transient current response of PMBLDC motor drive for proposed single neuron ANN based controller is moderated as compared to conventional drive.

Seventy percent of the population in Myanmar lives in rural areas. Although health workers are adequately trained, they are overburdened due to understaffing and insufficient supplies. Literature confirms that information and communication technologies can extend the reach of healthcare. In this paper, we present an SMS-based social network that aims to help health workers to interact with other medical professionals through topic-based message delivery. Topics describe interests of users and the content of message. A message is delivered by matching message content with user interests. Users describe topics as ICD- 10 codes, a comprehensive medical taxonomy. In this ICD-10 coded SMS, a set of prearranged codes provides a common language for users to send structured information that fits inside an SMS.

People are more mobile than ever before. People predominantly need information or help that they can not anticipate and plan for before they begin their journey. There is an abundance of information around us. But the users seek precise and fine–grained information that is not provided by the computing environment but required to carry out their tasks. Especially nomadic users have little choice than to call upon help from other people present in their vicinity. There are social issues (e.g. availability and interruptibility) along with the issues of relevance and reliability to find the most appropriate person to ask for any information or help. Identifying this person is still a challenge today. In this chapter we provide a thorough and grounded discussion of the state of the art of help systems that glean answers from human.We also present the software prototype Ubiquitous–Help–System (UHS) that has been developed to demonstrate how using a social network in combination with the user profile and preferences, can assist a nomadic user. The system assists the nomadic user to find people who can support him in a large scale ubiquitous computing environment.

When people need help they often turn to their social peers for reliable information, recommendation or guidance. It is often difficult to find someone in the vicinity for help or communicate with someone from a distant place who can provide reliable help. Conveying the actual context of the question during remote communication is a cumbersome task, especially when avoiding speech communication. Our approach selects and prioritizes the contextual data for a question, based on the question content.We have developed a prototype for mobile users - the Ubiquitous Help System (UHS) - that implements a mixed-initiative approach for capturing, selecting and prioritizing contextual information as well as for selecting a group of users to send the question. UHS processes the user questions for clues on what context to include and presents its suggestions to the user. Contextual data that can be retrieved using the available sensors on the mobile device is automatically included for sending to the receiving parties alongside the question.

Human activity is highly influenced by the context and environment of the user. Presence of other users in the vicinity can also influence the context of use and thus activity. In ubiquitous computing environments, people are surrounded by numerous computing devices helping them to carry out various tasks. However, users seek precise and fine-grained information that is not provided by the computing environment but required to carry out their tasks. Especially nomadic users have little choice than to call upon help from other people present in their vicinity. There are social issues (e.g. availability and interruptibility) along with issues of relevance and reliability to find the most appropriate person to ask for information. Identifying this person is still a challenge today. We have developed software prototype U-Help-System (UHS) to demonstrate how using a social network in combination with the user profile and preferences, can help nomadic person to approximate in selecting people that can support the user in a large scale ubiquitous computing environment.