An Integrated Testbed for Cooperative Perception with Heterogeneous Mobile and Static Sensors

Cooperation among devices with different sensing, computing and communication capabilities provides interesting possibilities in a growing number of problems and applications including domotics (domestic robotics), environmental monitoring or intelligent cities, among others. Despite the increasing interest in academic and industrial communities, experimental tools for evaluation and comparison of cooperative algorithms for such heterogeneous technologies are still very scarce. This paper presents a remote testbed with mobile robots and Wireless Sensor Networks (WSN) equipped with a set of low-cost off-the-shelf sensors, commonly used in cooperative perception research and applications, that present high degree of heterogeneity in their technology, sensed magnitudes, features, output bandwidth, interfaces and power consumption, among others. Its open and modular architecture allows tight integration and interoperability between mobile robots and WSN through a bidirectional protocol that enables full interaction. Moreover, the integration of standard tools and interfaces increases usability, allowing an easy extension to new hardware and software components and the reuse of code. Different levels of decentralization are considered, supporting from totally distributed to centralized approaches. Developed for the EU-funded Cooperating Objects Network of Excellence (CONET) and currently available at the School of Engineering of Seville (Spain), the testbed provides full remote control through the Internet. Numerous experiments have been performed, some of which are described in the paper

Hybrid Inspection Robot for Indoor and Outdoor Surveys

In this paper, simulation and experimental tests are reported for a hybrid robot being used for indoor and outdoor inspections. Automatic or tele-operated surveys can be performed by mobile robots, which represent the most efficient solution in terms of power consumption, control, robustness, and overall costs. In the context of structures and infrastructure inspection, robots must be able to move on horizontal or sloped surfaces and overpass obstacles. In this paper, the mechatronic design, simulations, and experimental activity are proposed for a hybrid robot being used for indoor and outdoor inspections, when the environmental conditions do not allow autonomous navigation. In particular, the hybrid robot is equipped with external and internal sensors to acquire information on the main structural elements, avoiding the need for experienced personnel being directly inside the inspection site, taking information from the environment and aiding the pilot to understand the best maneuvers/decisions to take. Given the current state of research and shortcomings worldwide, this paper discusses inspection robots taking into account the main issues in their use, functionality and standard systems, and how internal sensors can be set in order to improve inspection robots’ performances. On this basis, an illustrative study case is proposed

Human Body Posture Recognition Approaches: A Review

Human body posture recognition has become the focus of many researchers in recent years. Recognition of body posture is used in various applications, including surveillance, security, and health monitoring. However, these systems that determine the body’s posture through video clips, images, or data from sensors have many challenges when used in the real world. This paper provides an important review of how most essential ‎ hardware technologies are ‎used in posture recognition systems‎. These systems capture and collect datasets through ‎accelerometer sensors or computer vision. In addition, this paper presents a comparison ‎study with state-of-the-art in terms of accuracy. We also present the advantages and ‎limitations of each system and suggest promising future ideas that can increase the ‎efficiency of the existing posture recognition system. Finally, the most common datasets ‎applied in these systems are described in detail. It aims to be a resource to help choose one of the methods in recognizing the posture of the human body and the techniques that suit each method. It analyzes more than 80 papers between 2015 and 202

Use of Artificial Intelligence in Healthcare Delivery

In recent years, there has been an amplified focus on the use of artificial intelligence (AI) in various domains to resolve complex issues. Likewise, the adoption of artificial intelligence (AI) in healthcare is growing while radically changing the face of healthcare delivery. AI is being employed in a myriad of settings including hospitals, clinical laboratories, and research facilities. AI approaches employing machines to sense and comprehend data like humans has opened up previously unavailable or unrecognised opportunities for clinical practitioners and health service organisations. Some examples include utilising AI approaches to analyse unstructured data such as photos, videos, physician notes to enable clinical decision making; use of intelligence interfaces to enhance patient engagement and compliance with treatment; and predictive modelling to manage patient flow and hospital capacity/resource allocation. Yet, there is an incomplete understanding of AI and even confusion as to what it is? Also, it is not completely clear what the implications are in using AI generally and in particular for clinicians? This chapter aims to cover these topics and also introduce the reader to the concept of AI, the theories behind AI programming and the various applications of AI in the medical domain

Artificial Intelligence and Ambient Intelligence

This book includes a series of scientific papers published in the Special Issue on Artificial Intelligence and Ambient Intelligence at the journal Electronics MDPI. The book starts with an opinion paper on “Relations between Electronics, Artificial Intelligence and Information Society through Information Society Rules”, presenting relations between information society, electronics and artificial intelligence mainly through twenty-four IS laws. After that, the book continues with a series of technical papers that present applications of Artificial Intelligence and Ambient Intelligence in a variety of fields including affective computing, privacy and security in smart environments, and robotics. More specifically, the first part presents usage of Artificial Intelligence (AI) methods in combination with wearable devices (e.g., smartphones and wristbands) for recognizing human psychological states (e.g., emotions and cognitive load). The second part presents usage of AI methods in combination with laser sensors or Wi-Fi signals for improving security in smart buildings by identifying and counting the number of visitors. The last part presents usage of AI methods in robotics for improving robots’ ability for object gripping manipulation and perception. The language of the book is rather technical, thus the intended audience are scientists and researchers who have at least some basic knowledge in computer science

Reign Mobile Application for Hotspot Detection

Reign mobile hotspot detection system is a cross platform mobile application developed to help warn its users of hostile areas (i.e., areas prone to accident, flooding, kidnapping, civil unrest, etc.). It also has functionalities that allow users to report hazardous areas through a preconfigured e-mail, which includes the users current location and a description of the hazard being reported. The goal of this project is to explore the use of mobile computing, by means of mobile apps, to address some of the social and developmental challenges being experienced in Nigeria. Thus, we could adapt technology to improve social conditions as well as, possibly, save lives. The motivation for this project is the ubiquity of mobile computing, particularly when we consider that Nigeria with a population of over 140 million people is currently estimated to have a mobile broadband Internet penetration equivalent of about 30%. These users mostly connect through mobile devices with at least 100million unique mobile communication lines registered. The app was developed with HTML5 and JAVA programming languages, uses GPS coordinates to map locations and a push server to send alerts to registered users. Currently, the Android version of the app has been developed and is being tested. During the development and testing, we interacted with security and paramilitary institutions  like the Police, Federal Road Safety Service (FRSC) and the Nigerian Metrological Agency (NIMET) in order to ascertain areas that are prone to hazards. Preliminary tests in Lagos and Abuja confirm the functionality and usefulness of the app. Keywords: Mobile computing, hotspot detection, security hazards, crime detection and prevention, alerts

Infrastructuring bodies : Choreographies of power in the computational city

The aim of this chapter is to shed light on the power-related infrastructural dynamic that actualises in the interrelations of big data collection and the bodily movement of urbanites in contemporary cities. By drawing from Husserl’s and Merleau-Ponty’s phenomenologies of the body and combining them with recent theorisations on choreography, material media theory and critical technology studies, the authors address city dwellers’ embodied relations with mobile devices and ambient technologies as integral to the micro-, meso- and macro-level (re)production of urban infrastructures. By way of discussing the technologically mediated kinaesthesia and movement trajectories of lived bodies, the chapter develops a novel conceptualisation of urban choreography for exploring the mechanisms through which dwelling-in-the-city today functions in a globally extensive cybernetic feedback loop with profit-motivated and surveillant big data operations.acceptedVersionPeer reviewe