Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Evolution of IoT-enabled connectivity and applications in automotive industry: A review

The aim of this paper is to identify some of the challenges that need to be addressed to accelerate the deployment and adoption of smart health technologies for ubiquitous healthcare access. The paper also explores how internet of things (IoT) and big data technologies can be combined with smart health to provide better healthcare solutions.,The authors reviewed the literature to identify the challenges which have slowed down the deployment and adoption of smart health.,The authors discussed how IoT and big data technologies can be integrated with smart health to address some of the challenges to improve health-care availability, access and costs.,The results of this paper will help health-care designers, professionals and researchers design better health-care information systems.

Smart healthcare: Challenges and potential solutions using internet of things (IoT) and big data analytics

Patient monitoring is a pivotal part of the health care system nowadays, either at hospitals or at home. This paper proposes an intelligent patient monitoring system that automatically screens the patient’s health condition through various sensors. The data is then processed using a Raspberry Pi and useful information is saved to the IoT cloud. Primarily the system would be extracting the bio signal, ECG using an ECG sensor. Through continuous monitoring and graphical representation of the patient’s information, doctors/nurses/relatives can remotely check the patient’s condition. Furthermore, if the condition becomes critical, a notification is sent to the doctor/nurse/relative to inform them and either party will have the opportunity to start a video call.

IoT Based Patient Monitoring System Using ECG Sensor

Nowadays, Health care is considered as an important aspect of our everyday lives. To address the emerging health-related challenges, this research wprk has utilised the advanced digital technologies to develop a health tracking analyzer. Recently, the use of mobile phones and other gadgets has increased unprecedentedly by creating a significant impact on the mobile health care. Mobile Health applications serve a large number of consumers. The main aim of this research work is to create a health tracking analyzer so that any patient or anybody who is concerned about their health may be readily tracked by their doctors or health care providers. This loT -based device aids in critical situations by avoiding illness transmission and providing health diagnoses even when the doctor is at a considerable distance away from the patient. Many people are receiving therapy for a variety of issues, including heart disease. The proposed model plays a vital role in checking and storing the healthcare-related data in server by using a Wi-Fi Module. Furthermore, the proposed device tracks the heartbeat and temperature by using the detectors and also a microcontroller is attached to the sensor. To frequently update the condition of patient's, the microcontroller is linked with LCD display and Wi-Fi to transfer the information to the database. By employing an inter connection, the pulse rate and temperature can also be analyzed. The gadget will exchange the readings from the sensor to the cloud and the information gathered will also remain accessible. The proposed database analyzes the received information and alerts the patient through buzzer.

Indigenous Health Tracking Analyzer Using IoT

The popularity of Internet of Things is increasing day by day in the area of remote monitoring system. The remote monitoring systems include, vehicle or assets monitoring, kids/pets monitoring, fleet management, parking management, water and oil leakage, energy grid monitoring etc. In this paper, we have proposed an intelligent patient monitoring system for monitoring the patients' health condition automatically through sensors based connected networks. Several sensors are used for gathering the biological behaviors of a patient. The meaningful biological information are then forwarded to the IoT cloud. The system is more intelligent that can able to detect the critical condition of a patient by processing sensors data and instantly provides push notification to doctors/nurses as well as hospital in-charge personal. The doctors and nurses get benefited from this system by observing their corresponding patients remotely without visiting in person. Patients' relatives can also get benefited from this system with limited access.

Real time patient monitoring system based on Internet of Things

With the emergence of new technology and innovations, people are searching smarter ways to protect/monitor their properties remotely. In accordance to that, at present GPS based tracking system is frequently used in vehicle tracking, children/pet tracking, aircraft tracking, any personal belongings tracking, fleet management and so on. This paper introduces a Smart Anti-Theft Vehicle System based on Internet of Things (IoT) for monitoring the movement of any equipped vehicle from anywhere in real time. At the implementation of this system, Global Positioning System (GPS), Global System for Mobile Communication (GSM)/General Packet Radio Service (GPRS) and Microcontrollers are used to enable users for monitoring their vehicles in a convenient manner. This system provides the access to check the movement and control (emergency stop by closing the fuel line) vehicles remotely by using mobile application. The hardware prototype of the proposed system and the user application for monitoring and controlling vehicles are presented in this paper.

Smart anti-theft vehicle tracking system for Bangladesh based on Internet of Things

Face Recognition is one of the most emerging technology nowadays by which different types of system can be implemented in our regular life. It has a great scope to make our lives easier, and comfortable. This technology is using in various field. In this paper, an experimental approach is introduced to make a system which is based on the technology. The system can detect human face in real time. At the same time it recognize faces. Hence, this work aims to develop a system that detect and recognize individual faces in real time.

System Development using Face Recognition

Consensus is a significant part that supports the identification of unknown information about animals, plants and insects around the globe. It represents a small part of Deoxyribonucleic acid (DNA) known as the DNA segment that carries all the information for investigation and verification. However, excessive datasets are the major challenges to mine the accurate meaning of the experiments. The datasets are increasing exponentially in ever seconds. In the present article, a memory saving consensus finding approach is organized. The principal component analysis (PCA) and independent component (ICA) are used to pre-process the training datasets. A comparison is carried out between these approaches with the Apriori algorithm. Furthermore, the push down automat (PDA) is applied for superior memory utilization. It iteratively frees the memory for storing targeted consensus by removing all the datasets that are not matched with the consensus. Afterward, the Apriori algorithm selects the desired consensus from limited values that are stored by the PDA. Finally, the Gauss-Seidel method is used to verify the consensus mathematically.

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Big DNA Datasets Analysis under Push down Automata

The objective of the research is a stable gait generation on the level ground and some sloping ground of the 3-link biped robot with unbalanced masses using one actuator. We know the biped robot need actuator for stable walking on level ground. A biped robot with a torso model at least two actuators to achieve a stable walk. In the research we have investigated the only one motor which is very much challenging to achieve stable walking gait without the robot falls down, also there is used unbalanced masses where is very much difficult to achieve balanced walking. In this research, the numerical simulations show the robot with unbalanced masses can walk efficiently on level ground by only using one actuator. The robot can generate 2-period and 4-period gait without fall down. First, we introduced the 5-DOF (Degree of freedom) unbalanced masses model where used one actuator that walks the level ground. Second, describes the control system of Proportional-derivative (PD) controller between stance leg and torso, while the swing leg does not use any actuator and it does remain free. Third, we perform numerical simulations and show that the robot can generate a stable walk on level ground and some sloping ground by using one actuator. Furthermore, we conduct some parametric study to investigate the more natural human-like motion of the robot and achieved different results.

Jannat Binta Alam

Papers

Real time patient monitoring system based on Internet of Things

Smart anti-theft vehicle tracking system for Bangladesh based on Internet of Things

System Development using Face Recognition

Big DNA Datasets Analysis under Push down Automata

Stable walking of an underactuated bipedal robot with unbalanced masses using one actuator