Journal of Ambient Intelligence and Humanized Computing

https://link.springer.com/journal/12652

List of Papers (Total 100)

A knowledge based infrared camera system for invisible gas detection utilizing image processing techniques

An infrared camera system for real-time monitoring of invisible methane gas leakages is proposed, which can be used in production, transportation, and gas plants. Instead of using conventional lasers, a medium wavelength light-emitting diode (LED) with a center wavelength of approximately 3300 nm is used for the light source of the gas detector. We achieve compact cooling with...

SD-IoV: SDN enabled routing for internet of vehicles in road-aware approach

Proposing an optimal routing protocol for internet of vehicles with reduced overhead has endured to be a challenge owing to the incompetence of the current architecture to manage flexibility and scalability. The proposed architecture, therefore, consolidates an evolving network standard named as software defined networking in internet of vehicles. Which enables it to handle...

Using Therbligs to embed intelligence in workpieces for digital assistive assembly

Current OEM (Original Equipment Manufacturer) facilities tend to be highly integrated and are often situated on one site. While providing scale of production such centralisation may create barriers to the achievement of fully flexible, adaptable, and reconfigurable factories. The advent of Industry 4.0 opens up opportunities to address these barriers by decentralising information...

Modelling the effects of certain cyber-attack methods on urban autonomous transport systems, case study of Budapest

Based on the reviewed literature, the objective of the article is to investigate the most important cyberattack factors affecting the effectiveness of the connected and autonomous transport system. Accordingly, remotely implemented malicious interventions are in the focus of our study, especially considering cyberattacks on connected and autonomous vehicles. To introduce the...

Evaluation of radial basis function neural network minimizing L-GEM for sensor-based activity recognition

Sensor-based activity recognition involves the automatic recognition of a user’s activity in a smart environment using computational methods. The use of wearable devices and video-based approaches have attracted considerable interest in ubiquitous computing. Nevertheless, these methods have limitations such as issues with privacy invasion, ethics, comfort and obtrusiveness...

A real-time service system in the cloud

Recently, we have witnessed unprecedented use of cloud computing and its services. It is influencing the way software is built, as well as company’ resources such as servers, workstations or generally hardware are used. This paper aims to examine the benefits of cloud usage to support real-time service systems, using the Salesforce platform. First, we explore the meaning and the...

A study on user recognition using 2D ECG based on ensemble of deep convolutional neural networks

The risk of tampering exists for conventional user recognition methods based on biometrics such as face and fingerprint. Recently, research on user recognition using biometric signals such as electrocardiogram (ECG), electroencephalogram (EEG), and electromyogram (EMG) has been actively performed to overcome this issue. We herein propose a user recognition method applying a deep...

Big data of clinical manifestations combined with neuroelectrophysiologic features in the early diagnosis of motor neuron disease

Motor neuron disease/amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder characterised by loss of upper motor neurons (including the Betz cells of the motor cortex), and lower motor neuron, anterior horn cells of the spinal cord and brainstem nuclei. 5–10% in ALS is hereditary and sporadic, with an incidence of 2–3 per 100,000. ALS is a fatal disease...

Pulse coupled neural network based MRI image enhancement using classical visual receptive field for smarter mobile healthcare

With the rapid growth of medical big data, medical signal processing measurement techniques are facing severe challenges. Enormous medical images are constantly generated by various health monitoring and sensing devices, such as ultrasound, MRI machines. Hence, based on pulse coupled neural network (PCNN) and the classical visual receptive field (CVRF) with the difference of two...

A trust-based collaborative filtering algorithm for E-commerce recommendation system

The rise of e-commerce has not only given consumers more choice but has also caused information overload. In order to quickly find favorite items from vast resources, users are eager for technology by which websites can automatically deliver items in which they may be interested. Thus, recommender systems are created and developed to automate the recommendation process. In the...

Towards ambient assisted cities using linked data and data analysis

As citizens’ age increases, smart cities must adapt to help them to age properly. The objective of the City4Age project is to create the future ambient assisted cities that will help the citizens to deal with mild cognitive impairments (MCI) and frailty. In this paper we present two of the tools developed during the project. The first one is a city-wide context-manager, which...

Trust architecture and reputation evaluation for internet of things

Internet of Things (IoT) represents a fundamental infrastructure and set of techniques that support innovative services in various application domains. Trust management plays an important role in enabling the reliable data collection and mining, context-awareness, and enhanced user security in the IoT. The main tasks of trust management include trust architecture design and...

The pollutant concentration prediction model of NNP-BPNN based on the INI algorithm, AW method and neighbor-PCA

At present, the numerical prediction models fail to predict effectively due to the lack of basic data of pollutant concentration in a short term in China. Therefore, it is necessary to study the statistical prediction methods based on historical data. The traditional Back Propagation Neural Network (BPNN) has been used to predict the pollutant concentration. The missing data also...

MobileCogniTracker

As the population ages, cognitive decline is becoming a worldwide threat to older adults’ independence and quality of life. Cognitive decline involves problems with memory, language, thinking and judgement, thus severely compromising multiple aspects of people’s everyday life. Diagnosis of cognitive disorders is currently performed through clinical questionnaire-based assessments...