Face-It-Up: a scientific app for face processing using mobile devices and machine learning APIs

Defining standard application programming interfaces (APIs) plays an important role in Internet of Things (IoT) applications to achieve interpretability. Among different issues of designing APIs for IoT applications, this study focuses on the security issue of designing an API for people to access data about machines, sensors, and other objects collected in servers. To address the issue, this study shares the experiences of designing APIs for Taiwan uniform e-invoices. To prevent tax evasion, Taiwan government holds uniform invoice lottery every two months. Because invoice owners may win NT $10,000,000, the security of APIs to access e-invoices is critical. This study illustrates the security considerations in designing major APIs of Taiwan uniform e-invoices. In addition to common security issues, such as communication security, authentication, and non-repudiation, the APIs consider special security issues in different scenarios. The API for point of sales (POS) applications and ERP systems addresses the security consideration to transfer bulk data among machines; the e-invoice donation API proposes a scheme to restrict that each authorized person can only invoke the API through a specific device; the API for mobile applications considers the issue that misused mobile applications may transfer personal sensitive data and credentials to others secretly; the API for invoice exchanging allows people to obtain e-invoices immediately after transactions with their smart phones and to verify the integrity of the invoices. While this study gives examples of designing secure API for IoT applications from different perspectives, the paper can hopefully contribute to the security of IoT applications.

Internet of Things (IoT) is changing our life for the better. IoT covers various heterogeneous devices which are sensing the environment and/or monitoring a special event in the network. These devices are mostly mobile and are wirelessly connected either to each other or to the Internet. Additionally, IoT devices run many different applications and services which provide the consumers with data and information. This paper focuses on the design and implementation of an Application Programming Interface (API) for IoT services using the Named Data Networking (NDN). NDN provides an efficient and intelligent communication paradigm for constrained devices like in IoT and uses named content to transmit data in the network. We extend the IoT-NDN architecture and add a new layer for IoT services which will effectively improve the performance of communication between the heterogeneous devices and the services integrated in IoT-NDN. Furthermore, we show the usage of our API and give a small example of network time synchronisation on IoT devices. This illustrates how flexible and lightweight is our approach for several services implemented on heterogeneous devices in IoT.

Face recognition in humans is a complex cognitive skill that requires sensitivity to unique configurations of eyes, mouth, and other facial features. The Thatcher illusion has been used to demonstrate the importance of orientation when processing configural information within faces. Transforming an upright face so that the eyes and mouth are inverted renders the face grotesque; however, when this "Thatcherized" face is inverted, the effect disappears. Due to the use of primate models in social cognition research, it is important to determine the extent to which specialized cognitive functions like face processing occur across species. To date, the Thatcher illusion has been explored in only a few species with mixed results. Here, we used computerized tasks to examine whether nonhuman primates perceive the Thatcher illusion. Chimpanzees and rhesus monkeys were required to discriminate between Thatcherized and unaltered faces presented upright and inverted. Our results confirm that chimpanzees perceived the Thatcher illusion, but rhesus monkeys did not, suggesting species differences in the importance of configural information in face processing. Three further experiments were conducted to understand why our results differed from previously published accounts of the Thatcher illusion in rhesus monkeys.

Pervasive healthcare services have undergone a great evolution in recent years. The technological development of communication networks, including the Internet, sensor networks, and M2M (Machine-to-Machine) have given rise to new architectures, applications, and standards related to addressing almost all current e-health challenges. Among the standards, the importance of OpenEHR has been recognized, since it enables the separation of medical semantics from data representation of electronic health records. However, it does not meet the requirements related to interoperability of e-health devices in M2M networks, or in the Internet of Things (IoT) scenarios. Moreover, the lack of interoperability hampers the application of new data-processing techniques, such as data mining and online analytical processing, due to the heterogeneity of the data and the sources. This article proposes an Internet of Medical Things (IoMT) platform for pervasive healthcare that ensures interoperability, quality of the detection process, and scalability in an M2M-based architecture, and provides functionalities for the processing of high volumes of data, knowledge extraction, and common healthcare services. The platform uses the semantics described in OpenEHR for both data quality evaluation and standardization of healthcare data stored by the association of IoMT devices and observations defined in OpenEHR. Moreover, it enables the application of big data techniques and online analytic processing (OLAP) through Hadoop Map/Reduce and content-sharing through fast healthcare interoperability resource (FHIR) application programming interfaces (APIs).

The framework described in this work is a propelled explication to diagnosis of the health condition of the individuals who is affecting from arthritis disease. The innovation underlying this is the Internet of Things (IoT), a propelled system in the current trend to combine sensor data to the visualization platform for improved comprehension. In this work, we fabricated a thin film‐based bio‐sensor for detecting uric acid (UA) in the blood which is used to diagnose the arthritis disease. The fabricated sensor is integrated with node microcontroller unit (MCU) unit to store the uric acid content data where it is processed and recorded. The logged information can be forwarded by utilizing IoT technology using Thing Speak application programming interfaces (APIs) key and the information refreshed from the framework can be available in the cloud connector. The data for visualization can be obtained by API, validated with the private key, and accessed using Thing Speak APIs on multiple platforms such as mobile, tablet, and laptop connected to the internet. So, in summary, Thing Speak API Handler ensures the legitimacy of data retrieval from the cloud and visualization across several platforms.

The growth of the Internet of Things (IoT) application within the health- and wellbeing domain enables individuals to monitor their health. Acquired data can be used privately, contribute to clinical databases, or for research. The amount of health and wellbeing tracking devices introduces complexity in data aggregation and scattered overviews. Few services exist to aggregate health data. Current services raise privacy concerns. Consume is a service for aggregating authentication and authorisation for Application Programming Interfaces (APIs). Consume aims at research and allows to add existing and custom APIs on-the-fly without restarting services.

As mobile devices and applications continue to grow in popularity worldwide, so do the rise of cybersecurity attacks and threats to daily users of both Android and iOS devices on a widespread basis. These attacks not only target mobile devices at the application level but also at the Operating System (OS) device level and Application Programming Interface (API) level extending the Internet of Things (IoT). This paper will address the security vulnerabilities in Android Operating System at the intersection of APIs, device OS, and application-level vulnerabilities by identifying an intersection of commonalities to create mitigation strategies and best practices for securing mobile devices for organizations. The study recommends the adoption of processes of authentication on mobile devices and web-based log-ins as well as access control mechanisms that can mitigate the overlapping security challenges of APIs, mobile devices OS and applications using optimal resources to enhance security. This was achieved by analyzing the threats and vulnerabilities of API.KeywordsAPIsSecurity vulnerabilitiesMobile OSAndroidiOS

The articles in this special section address new applications supported by the Internet of Things. The Internet of Things (IoT) is seen as a set of vertical application domains that share a limited number of common basic functionalities. In this view, consumer-centric solutions, platforms, data management, and business models have to be developed and consolidated in order to deploy effective solutions in the specific fields. The availability of low-cost general-purpose processing and storage systems with sensing/actuation capabilities coupled with communication capabilities are broadening the possibilities of IoT, leading to open systems that will be highly programmable and virtualized, and will support large numbers of application programming interfaces (APIs). IoT emerges as a set of integrated technologies — new, exciting solutions and services that are set to change the way people live and produce goods. IoT is regarded by many as a fruitful technological sector in order to generate revenues. IoT covers a large wealth of consumer-centric technologies and is applicable to an even larger set of application domains. Innovation will be nurtured and driven by the possibilities offered by the combination of increased technological capabilities, new business models, and the rise of new ecosystems. Addresses several promising approaches to sensors, actuators, and new consumer devices.

Internet of Things (IoT) globally is an emerging technology enabling the exchange of knowledge and services. But over the years, security in IoT has become an issue. This paper shows a way of including security to daily-based applications by the use of voice biometrics. The voice of a user is stored and authenticated using an API (Application Programming Interface) called “VoiceIT”. This method involves the use of Python as the main coding language and uses many libraries such as the Google Speech library for speech synthesis that converts a speech to a text format. The processing of the code is done using Raspberry Pi 3. The implementation of this experiment proves useful for increased security in an advanced IoT system.

Provisioning of applications and value-added services for mobile (remote) monitoring and access to measurements data is supported by advanced communication models such as Internet of Things (IoT). IoT provides ubiquitous connectivity anytime and with anything. IoT applications are able to communicate with the environment, to receive information about its status, to exchange and use the information. Identification of generic functions for monitoring management, data acquisition, and access to information provides capabilities to define abstraction of transport technology and control protocols. This chapter presents an approach to design Web Services Application Programming Interfaces (API) for mobile monitoring and database access. Aspects of the Web Services implementation are discussed. A traffic model of Web Services application server is described formally. The Web Services application server handles traffic of different priorities generated by third party applications and by processes at the database server's side. The traffic model takes into account the distributed structure of the Web Services application server and applies mechanisms for adaptive admission control and load balancing to prevent overload. The utilization of Web Services application server is evaluated through simulation.

The Internet of Things (IoT) is a remarkable data producer and these data may be used to prevent or detect security vulnerabilities and increase productivity by the adoption of statistical and Artificial Intelligence (AI) techniques. However, these desirable benefits are gained if data from IoT networks are dependable—this is where blockchain comes into play. In fact, through blockchain, critical IoT data may be trusted, i.e., considered valid for any subsequent processing. A simple formal model named “the Mirror Model” is proposed to connect IoT data organized in traditional models to assets of trust in a blockchain. The Mirror Model sets some formal conditions to produce trusted data that remain trusted over time. A possible practical implementation of an application programming interface (API) is proposed, which keeps the data and the trust model in synch. Finally, it is noted that the Mirror Model enforces a top-down approach from reality to implementation instead of going the opposite way as it is now the practice when referring to blockchain and the IoT.

The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing and wireless grids has resulted in the widespread deployment of relatively immature technology. These technologies, which will primarily use 5G wireless communication networks, are becoming popular because they can be deployed quickly with little infrastructure and lends themselves to environments utilizing numerous internet connected devices (ICD). There are, however, many significant challenges faced by security designers, engineers and implementers of these networks in ensuring that the level of security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected by a robust security architecture due to these technologies being plagued with security problems. The authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new information system platforms. This article identifies an authentication process required for these ICDs, which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud network through a wireless grid authentication process. The purpose of this article is to begin to hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and mobile edge computing clouds to create this new IoT architecture. An authentication process developed from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors depending on their capability to handle five primary functions: management of identification [ID] and presence, permissions management, data transferability, application-programming interface [API] and security.

One of the problem with data loggers (data recording tools) from solar panels is that their use is limited to the capacity of the internal battery as a power supply. So the higher the capacity of the internal battery, the longer the data logger can operate and vice versa. It is necessary to have a feature to set the active and inactive time of the data logger in the process of recording data to improve the efficiency of internal battery usage. In this paper, an alternative solution is presented, namely through setting the active and inactive time of the data logger by using IoT (Internet of Things) based on the current time, sunrise time, and sunset time through the API (Application Programming Interface). The test results show that the device can monitor the parameters of solar panel voltage, current, power, temperature and humidity and internal battery voltage in real-time through a mobile device. With this method, the amount of internal battery power savings is 65.56%,68.78%, and 69.21 % with the time interval for recording data every 1 minute, 5 minutes and 10 minutes respectively, which is tested for 24 hours.

SummaryThe increasing popularity of Internet of Things (IoT) services causes tremendous growth of the amount of produced data. These data must be effectively stored and retrieved by the IoT service providers. The solution is to access the data through application programming interfaces. The paper focuses on the problem of designing an effective data storage service for IoT, which will be available through the universal application programming interface. We propose and analyze eight variants of the distributed data storage service that differ in the database structure, that is, the hierarchical structure based on Data‐Oriented Network Architecture or the flat structure based on distributed hash table, the type of stored records, and the memory management algorithm that decides about using cache or base memory. The proposed solutions have been evaluated in the comprehensive simulation studies. The obtained results confirmed the effectiveness of the preferred solution with Dynamic Routing Records stored in the cache memory. Copyright © 2016 John Wiley & Sons, Ltd.

Industry 4.0 is considered as the fourth revolution in industrial sector that represents the digitization of production process in a smarter way. Industry 4.0 refers to the intelligent networking of machines, their processes, and infrastructure, as well as the use of information and computer technology to transform industry. The technologies like industrial internet of things (IIoT), big data analytics, cloud computing, augmented reality and cyber security are the main pillars of industry 4.0. Industry 4.0, in particular, is strongly reliant on the IIoT that refers to the application of internet of things (IoT) in industrial sector like smart grids (SG). IoT can be deployed in different sections of smart grids that include electricity generation, transmission, distribution and its utilization at customer side. However, the key obstacles that deployment faces are theft detection and localization in smart grids. Electricity theft causes huge losses to the electricity providers and in turn contributes in increasing the fiscal deficit of the government. Therefore, this paper provides an IoT based solution that implements a system which automatically checks for electricity theft in between the regional transformer and customer side. The system also sends the latitude and longitude coordinates of the place where the theft has been detected on to the thingspeak cloud platform. Further, the exact location of the theft has been displayed on the webpage using geolocation application programing interface (API) on Google maps. The proposed system can be easily integrated in the smart grid network structure and helps companies to increase their business.