In recent years, with the development of advanced mobile applications, people’s various daily behavior data, such as geographic location, social information, hobbies, are more easily collected. To process these data, data cross-boundary fusion has become a key technology, and there are some challenges, such as solving the problems of the cross-boundary business integrity, cross-boundary value complementarity

With the pervasiveness of GPS-enabled devices, a considerable number of GPS traces are accumulating continuously and unobtrusively in online communities. However, almost all current applications directly use raw GPS data, such as coordinates and time stamps, without interpreting these data. Thus far, online communities cannot offer much support to users in terms of recommending geospatial locations

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are

Although spatial and temporal information has often been considered to improve recommendation performances, existing multi-criteria recommender systems often neglect to leverage spatial and temporal information. Also, it is a non-trivial task to simultaneously apply such information to recommendation services since the factors have interrelations to each other. In this paper, we propose a multi-criteria

Abstract CasAware is an Ambient Assisted Living platform, developed within an Italian research project, with the aim to improve the level of comfort and well-being of inhabitants of a house, while optimizing the energy consumption. A key feature, for successful realization of such a platform, is its capability to interoperate with other IoT platforms, which can augment CasAware with additional services

This paper argues that energy consideration should be central to software development. It speculates that including the notion of energy awareness in programming language design for domain specific languages (DSLs) is a novel way in which energy-aware and energy-efficient applications can be developed. It outlines the design criteria and rationale for using a language-focused approach for energy-awareness

On November 20, 2018 at 11 am, Andrés Camilo Jiménez Alvarez defended his Ph.D. thesis entitled Decentralized navigation model for multiagent cooperative robotic systems at the Distrital University Francisco José de Caldas. Andrés Camilo Jiménez Alvarez presented his dissertation in a public open event held in the “Wise Caldas Auditory”, and was able to expose and defend all his research, it was approved

Internet of Things (IoT) based systems have revolutionised the way real world systems are inter-connected through internet. At present the application of IoT based systems is extend to real time detection and warning system. However, cost has been a major factor for development and implementation of IoT systems. Considering the cost, ease of implementation, this paper proposes a low cost yet efficient

The number of elderly is increasing in recent years. According to the United Nations (UN), in 2050 there will be 2.1 billion people above 60 years of age worldwide. In addition, the World Health Organization (WHO) reported that more than 1 billion people live with some form of disability, the leading causes of which are chronic diseases and accidents. Thus, many opportunities for the application of

As the Internet of Things (IoT) penetrates different domains and application areas, it has recently entered also the world of robotics. Robotics constitutes a modern and fast-evolving technology, increasingly being used in industrial, commercial and domestic settings. IoT, together with the Web ofThings (WoT) could provide many benefits to robotic systems. Some of the benefits of IoT in robotics have

The presence of pollutants in the air has a direct impact on our health and causes detrimental changes to our environment. Air quality monitoring is therefore of paramount importance. The high cost of the acquisition and maintenance of accurate air quality stations implies that only a small numberof these stations can be deployed in a country. To improve the spatial resolution of the air monitoring

Abstract Air quality is a critical matter of concern in terms of the impact on public health and well-being. Although the consequences of poor air quality are more severe in developing countries, they also have a critical impact in developed countries. Healthcare costs due to air pollution reach $150 billion in the USA, whereas particulate matter causes 412,000 premature deaths in Europe, every year

Precision agriculture has different strategies to collect, process and analyze different types and nature data to be able to make decisions that improve the efficiency, productivity, quality, profitability and sustainability of agricultural production. Specifically, crop sustainability is directlyrelated to reducing costs for farmers and minimizing environmental impact. In this paper, an application

This paper presents a detection method of Alternaria solani in tomatoes. Several machine learning models were used to detect the pathogen, such as the implementation of decision trees and ensemble learning methods. The use of these methods requires the acquisition of large volumes of data and adequate preprocessing of this data. For the presented study the dataset of hyperspectral measurements of two

Large scale real-time water quality monitoring system usually produces vast amounts of high frequency data, and it is difficult for traditional water quality monitoring system to process such large and high frequency data generated by wireless sensor network. A real-time processing and early warning system framework is proposed to solve this problem, Apache Storm is used as the big data processing

Smartphones, with built-in array of sensors, provide an opportunity to ubiquitously collect user’s behavioral data. This leads to variety of founding applications that identifies interesting patterns in the smartphone data to learn human behavior. In this paper, we propose an approach that enhancesthe productivity of individual’s by unobtrusively learning their routine through smartphones. We design

This manuscript presents a new approach to the use of Internet of Things technologies in a practical and significant way in the system of smart data loggers. The subject of research is the observation and control of the microclimate using Internet of Things technology and smart sensor nodes. It isknown that working environments take into account the ambient parameters that influence the concentration

Ambient Assisted Living (AAL) systems are increasingly being deployed in real-world environments and for long periods of time. This significantly challenges current approaches that require substantial setup investment and cannot account for frequent, unpredictable changes in human behaviours, health conditions, and sensor deployments. The state-of-the-art methodology in studying human activity recognition

Abstract We are moving towards ‘smart’ world in which industries, such as healthcare, smart cities, transportation, and agriculture have started using IoT (Internet of Things). These applications involve huge number of sensors and devices that generate high volume of real time data. To perform useful analytics on this data, location and spatial awareness characteristics of devices need to be considered

People spend their leisure time on cultural and historical stories by visiting exhibitions and museums with family members and friends. This small gathering establishes a voluntary platform to engage in activities and share experiential knowledge. Since members of a small group tend to have diversepreferences, both individual and group preferences should be considered for a cohesive and harmonious

Formal modeling and analysis of human behavior can properly advance disciplines ranging from psychology to economics. The ability to perform such modeling has been limited by a lack of ecologically-valid data collected regarding human daily activity. We propose a formal model of indoor routine behavior based on data from automatically-sensed and recognized activities. A mechanistic description of behavior

The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order

Vehicular networking has gained considerable interest within the research community and industry. The automotive industry is supporting the notion of pervasive connectivity by agreeing to equip vehicles with devices required for vehicular ad hoc networking. Equipped with these devices, mobile nodesin vehicular ad hoc networks (VANETs) are capable of hosting many types of applications as services for

Currently, smartwatches are mainly used as an extension of smartphones. However, equipped with various motion sensors, they are also effective devices for human activity recognition, particularly for those involving hand and arm movements. In this paper, we investigate the smoking recognition problem with motion sensors on smartwatches using supervised learning algorithms. For this purpose, we collected

Abstract Predicting the footfall in a new brick-and-mortar shop (and thus, its prosperity), is a problem of strategic importance in business. Few previous attempts have been made to address this problem in the context of big data analytics in smart cities. These works propose the use of social network check-ins as a proxy for business popularity, concentrating however only on singular business types

Abstract In this paper, we present our study regarding facilitating storytelling of older adults living in the nursing home with their children. The paper was driven by the following research questions: (1) What life stories would the older adults like to share? And (2) In which ways, could design enable the older adults to tell their stories? We designed a tangible device named Slots-Story, and conducted

Smart environments can already observe the actions of a human through pervasive sensors. Based on these observations, our work aims to predict the actions a human is likely to perform next. Predictions can enable a robot to proactively assist humans by autonomously executing an action on their behalf. In this paper, Action Graphs are introduced to model the order constraints between actions. Action

The rapid growth of the world’s population increases the demand for more efficient management of ambient and environment. To address the demand, modern technologies are applied to enhance the surrounding to become more intelligent and efficient such as the development of intelligent building (IB) via the enhancement of the building with interconnected sensors, advanced event detection mechanism and

Diabetes is among the most common medical issues which people are facing nowadays. It may cause physical incapacity or even death in some cases. It has two core types, namely type I and type II. Both types are chronic and influence the functions of the human body that regulate blood sugar. In the human body, glucose is the main element that boosts cells. However, insulin is a key that enters the cells

Smart homes equipped with ambient wireless sensor networks provide new opportunities to help older adults age-in-place, improve their quality of life and help better manage their health and wellness. In this paper, we present a methodology that estimates occupants’ status as active, sedentary, in-bed, out-of-home and unobservable, their location in the house, and their daily activities related to overall

First and the foremost, universities and businesses will need to address new or amplified existing societal issues, such as poverty, unemployment, isolation, mental health problems, a lack of digital literacy and many others and re-invent their institutional roles in society For organisations to embrace ethically and socially responsible thinking, the provision of social responsibility education is

Over the past eleven years of its life, our Journal has been supported by a large number of colleagues who contributed with their time and expertise to assess the quality of the submissions to JAISE and helped decide which papers qualify to be published. These reviewers are an important part of the JAISE community and we would like to explicitly thank all of them for their valuable contributions. The

Andrés Muñoz a, Juan Carlos Augusto b, Vincent Tam c and Hamid Aghajan d a Polytechnic School, Universidad Católica de Murcia, Spain b Department of Computer Science and Research Group on Development of Intelligent Environments, Middlesex University, UK c Department of Electrical and Electronic Engineering, Faculty of Engineering, The University of Hong Kong, China d imec, IPI, Department of Telecommunications

Recently, technological advancements have led to the use of autonomous devices such as robotic devices to facilitate gait rehabilitation and assistance. While autonomous devices have become faster, “smarter”, stronger, more accurate and reliable, challenges remain in adaptability, decision making and robustness to changing and uncertain situations. To address these shortfalls and improve flexibility

The public health implications of growing numbers of older adults at risk for dementia places pressure on identifying dementia at its earliest stages so as to develop proactive management plans. The prodromal dementia phase commonly identified as mild cognitive impairment is an important target for this early detection of impending dementia amenable to treatment. In this paper, we propose a method

Written by an outstanding group of experts in the field, this book presents an exciting and fresh compilation of the last advances and developments in one of the most popular nanostructured materials, nanoporous anodic alumina. The electrochemical and synthetic methods, as well as characterization techniques and applications will be discussed in detail throughout this book. Nanoporous anodic alumina

Rapid population aging and the availability of sensors and intelligent objects motivate the development of healthcare systems; these systems, in turn, meet the needs of older adults by supporting them to accomplish their day-to-day activities. Collecting information regarding older adults daily activity potentially helps to detect abnormal behavior. Anomaly detection can subsequently be combined with

Adaptive context-aware learning environments (ACALEs) can detect the learner’s context and adapt learning materi-als to match the context. The support for context-awareness and adaptation is essent ...