Remote Intelligence Research Articles

Improving Therapeutic Adherence in Oncohematological Patients with a Software Application: The Margherita Study

Background: Therapeutic adherence plays a key role in treatment outcomes. Novel technologies have the potential to support patients (pts) throughout their treatment journey, thereby improving therapeutic adherence. Additionally, technology support can aid in the collection of patient-reported outcomes (PROs). Aim of the study: To evaluate whether a software application specifically designed to support oncohematological pts could improve therapeutic adherence. A comparison with a matched historical cohort was also performed. This study supports the registration of RITA as a class IIA medical device. Methods: We conducted a phase II monocentric prospective study, enrolling oncohematological pts affected by different diseases. Pts were monitored and supported in managing complications by using a specifically designed APP, called RITA (Remote Intelligence for Therapeutic Adherence) for 3 months. Besides, RITA allowed collection of ePROs and quality-of-life (QoL) data, through the EQ-5D-5L questionnaire, activity of daily life (ADL) and instrumental activity of daily life (IADL) scale data. RITA supported pts, by providing informations for managing reported complaints. Pts were enabled to report the following vital parameters: blood pressure, heart rate, oxygen saturation, respiratory rate, temperature, glycaemia, and weight. RITA also connected patient and doctor when necessary. The primary endpoint of the study was therapeutic adherence measured as at least the 80% of the relative dose intensity (defined as the ratio of delivered dose intensity to the prescribed referenced dose intensity, expressed as a percentage) during the study period. Results: Sixty-two pts received support with RITA (APP group). Median age was 72 years (range 19-94), with 45 patients having a lymphoproliferative disease and 17 patients having a myeloproliferative disease. Ten pts were enrolled at treatment start, while 52 were still on treatment. Thirty-six (58%) pts used the APP more than 14 days, and the median number of accesses was 3.5 for patients ≤ 50 years, and 10 for patients > 50 years. Predefined therapeutic adherence (>80%), was 82.8%, 81.5%, and 85.2% after 1, 2, and 3 months, respectively. When compared with the matched historical controls, the likelihood of being adherent seems to be higher at all time points in the APP group pts; after 3 months, the OR for therapeutic adherence in multivariate analysis of the APP group was 3.02 (95% CI, 1.04-8.76) respect to the historical control. In the APP group, 12 emergency room accesses by 10 patients were recorded, with the following causes: hearth failure (4), infection (4), atrial fibrillation (2), asthenia (1), and hyperbilirubinemia (1). Overall, 4626 access to the APP were registered, 2410 in the older half, and 2216 in the younger half of the population. A total of 1560 ePROs were recorded, with 1080 being grade 1, 370 grade 2, and 26 grade 3. The most frequent complaints were fatigue, reported 876 times, then itching (123 times), decrease in vision (107 times), insomnia (58 times), declivous edema (42 times), flu-like symptoms (43 times), cough (37 times), diarrhea (33 times), pain (33 times), anxiety (31 times), fever (36 times), tingling (23 times), pollakiuria (19 times), nervousness (17 times), and dysgeusia (17 times). The following clinical parameters were recorded: blood pressure (1652 times), heart rate (1538 times), oxygen saturation (1145 times), respiratory rate (227 times), temperature (1357 times), glycaemia (285 times), and weight (1439 times). The EQ-5D-5L questionnaire was completed by 50 (81%) pts at baseline, and 16 (26%) pts at 3 months. ADL and IADL questionnaires were completed by 43 (69%) pts at baseline, and 14 (23%) pts at 3 months. No side effects related to the APP were recorded. Conclusions: This is the first study demonstrating the efficacy of an APP in improving the therapeutic adherence in oncohematological patients. Furthermore, RITA allowed the collection of relevant ePROs, clinical parameters, and QoL data. Interestingly, several grade 1 and 2 ePROs were recorded, suggesting that RITA can improve the collection of low-grade adverse events respect to traditional methods. (Founded by Advice Pharma, NCT05260203).

Are software automation and teleworker substitutes? Preliminary evidence from Japan

AbstractDigital technology is reshaping workplaces by enabling spatial separation of offices, known as telework, or remote intelligence (RI) and by facilitating automation of service sector tasks via artificial intelligence (AI). This paper is the first attempt to empirically investigate whether AI and RI are complements or substitutes in the service sector. It uses a worker‐level panel of surveys collected from around 10,000 workers from pre‐COVID‐19 pandemic to late 2022. We find preliminary evidence that suggests that AI and RI are complements rather than substitutes. The evidence comes first from the positive correlation of investments in AI‐promoting and RI‐promoting software at the firm and worker level, and second from the positive correlation of workers' expectations regarding telework and software automation. The evidence is far from definitive but suggests that the complement‐substitution question is a fruitful line for future research.

Guest Editorial: Introduction to Heterogeneous Robotic Systems in 5G and Beyond Networks

Remote intelligence in the application of robotics and the autonomous system relies heavily on seamless wireless connections. The 5G mobile network technology meets traditional manufacturing enterprises' application requirements for wireless networks based on robot transformation and upgrading, robot interconnection, and remote interactive applications in production. However, there exists many challenging 5G communication issues, such as different communication protocols in the system varies with different robots and no dis-ruptive changes to the physical layer.

Networked Twins and Twins of Networks: An Overview on the Relationship Between Digital Twins and 6G

Digital twin (DT) is a promising technology for the new immersive digital life with a variety of applications in areas such as Industry 4.0, aviation, and healthcare. Proliferation of this technology requires higher data rates, reliability, resilience, and lower latency beyond what is currently offered by 5G. Thus, DT can become a major driver for 6G research and development. Alternatively, 6G network development can benefit from DT technology and its powerful features such as modularity and remote intelligence. Using DT, a 6G network (or some of its components) will have the opportunity to use artificial intelligence more proactively in order to enhance its resilience. DT's application in telecommunications is still in its infancy. In this article, we highlight some of the most promising research and development directions for this technology.

Legal professionalism in a context of Uberisation

ABSTRACT From around the millennial turn, Australia was to the fore among common law countries in the liberalisation of legal practice with a range of radical reforms, such as the ownership of firms by non-lawyers and listing on the stock exchange. Albeit not peculiar to Australia, technological innovations, including remote working, digitalised platforms and artificial intelligence (AI), are also dramatically changing the way law is practised. Invariably motivated by profit maximisation, the impact of these reforms poses discomfiting questions for the underlying values of legal professionalism. This article will overview the reforms that have occurred, drawing on a small study of NewLaw firms in Australia and the UK, to illustrate how the “Uberisation” of contemporary legal practice is contributing to a new incarnation of postprofessionalism. The article will also show how the injunction to work at home in response to COVID-19 has given “Uberisation” an adrenalin shot in the arm.

High Frequency Solid State Transformer Design Considerations for Power Systems Applications

The conventional power frequency (50 or 60 Hz) transformers are economical, highly reliable and quite efficient but they suffer with certain drawbacks like sensitive to harmonics, voltage drop under load, no protection from system disruptions and overloads, poor performance under dc offset load unbalances and no scope to improve power factor. These transformers with copper wound wires on iron cores are unable to respond to control signals as power generations become distributed and intermittent. So, the need of electronic based regulated power supply with software based remote intelligence has become essential. Also, to easily connect the new energy sources to the grid and to improve the power quality by harmonic filtering, voltage sag correction and highly dynamic control of the power flow, a new type of transformer based on power electronics, known as SST has been introduced. The SST realizes voltage transformation, galvanic isolation, power quality improvements such as instantaneous voltage regulation, voltage sag compensation and power factor correction. It is a collection of high-powered semiconductor components, high frequency power transformer and control circuitry which is used to provide a high level of flexible control to power distribution networks. The SST is a high frequency switched Power Electronic Devices (PEDs) based transformer with high controllability that enables flexible connectivity between existing medium voltage power distribution network, low voltage AC residential system and envisioned DC residential system. In this paper a systematic constructional detail of a SST with a power rating of 2 kVA, operating frequency of 20 kHz and voltage rating of 600/60 V as a scaled-down prototype used for power converter topologies is presented. The design is simple and it avoids the difficulty of choosing massive amounts of empirical parameters.

Right hemicolectomy with D3 lymph node dissection for right-sided transverse colon cancer using the Senhance robotic system: a case report

BackgroundThe evolution of remote systems and artificial intelligence technology has led to increase in robotic surgeries. One system used in this case report is the Senhance robotic system. The most important premise for using robotic surgery in cancer therapeutics is to ensure oncological safety. Similar to conventional laparoscopic surgery, robotic surgery needs to be a reliable and secure surgical procedure, such as complete mesocolic excisions with central vascular ligations in Western countries or D3 lymph node dissections (dissection of the lymph nodes that locates from the origin to the terminal branch of the main feeding artery of cancer) in Japan.Case presentationA 76-year-old man underwent clinical examination for severe anemia. He was diagnosed with transverse colon cancer of tumor (T)3, node (N)1a, metastasis (M)0 cancer stage IIIA. A right hemicolectomy with D3 lymph node dissection using the Senhance surgical system was performed. The operative time was 313 min and the estimated blood loss was 5 ml. He was discharged from our hospital 12 days after the surgery without any complications. What is the remarkable of this report, not only mobilization of right colon but also D3 lymph node dissection and vascular ligation were performed intraperitoneally by using Senhance robotic system as conventional laparoscopic surgery. We tried using fourth robotic arm to accomplish lymphadenectomies and middle colic artery dissection. A right hemicolectomy with D3 dissection using the Da Vinci surgical system was reported. Another report of a right hemicolectomy performed with the Senhance robotic system was identified; however, in that study, lymph node dissections were not performed intraperitoneally.ConclusionsTherefore, to our knowledge, this is the first report using the Senhance robotic system for right hemicolectomy with D3 dissection. We hope that our case report will assist in the establishment of this robotic procedure in surgical practice.

Guest Editorial: Digitally Transforming Oil Fields With Connected, Intelligent Hardware

In recent years, the oil and gas industry has placed significant emphasis on digital transformation. For most early adopters, this journey began with real-time monitoring and remote operation of equipment. This has been followed by the increasing application of modern data science techniques in order to extract actionable insight from the growing volumes of data. The emergence of highly scalable data storage and compute power has provided a step change in the ability to derive actionable insights from data and perform simulations at a scale previously inaccessible. What we derive from this combination allows us to deliver new levels of performance and efficiency. But, in addition to these now well recognized elements of the digital transformation, there is a need to evolve our industry hardware through the application of enhanced edge computing and the application of intelligence at the edge. There will, of course, continue to be engineering innovation in our hardware, resulting from creative new designs that result in new functional features, cost efficiency, enhanced reliability and greater operational performance. But there are now myriad opportunities to enhance hardware in ways that maximize the value of data capture. Thus, the emergence of connected, intelligent hardware is key to realizing the vision of the digitalized oil field. Connected, Intelligent Hardware Explained Much conventional hardware has little to no digital enablement or means of monitoring its own function or state. In a first step, it is largely trivial to make it connected to cloud-based data stores, thus enabling the use of modern data analysis techniques such as artificial intelligence (AI) and machine learning (ML). Each piece of hardware in this scenario will benefit from remote intelligence to enrich its capabilities. Intelligent hardware takes the “connected” concept in another direction and refers to equipment with embedded edge computing that can host models and algorithms, creating capabilities beyond remote intelligence. These machines can now take advantage of both edge and cloud digital capabilities to learn and gain intelligence, thus continuously improving operational performance and service delivery. By populating oil fields with connected and intelligent hardware, operators gain access to optimized, secure, and sustainable operations. Connected and intelligent hardware enables advanced planning, real-time performance optimization, and higher levels of automation and health management. It is a critical part of a broader architecture that is adapted to problems where latency, communications fallibility, and system reliability are important considerations that make a central command-and-control approach inappropriate.

A Cognitive-Driven Building Renovation for Improving Energy Efficiency: The Experience of the ELISIR Project

In the last few years, the technology re-evolution has deeply transformed several aspects of everyday life. For sure, one technology with a strong impact is the so-called Internet of Things (IoT). The IoT paradigm made it possible to break down the data barrier between the vertical domains on which the traditional information and communication technology (ICT) world was organized. Recently, the designers of home automation systems have begun looking to the IoT paradigm to ease the deployment of systems that are able to collect data from different plants. Such a situation has driven further evolution from the traditional automation system, where logic is defined by the programmer or by the user, to a cognitive system that is able to learn from the user’ habits regarding what should be the best configuration of plants. Several countries are funding renovations of public and private buildings for improving energy efficiency. Generally, such renovations are only focusing on the structure of the building and of its energy performance (e.g., the thermal envelope, window units, air-conditioning plants, and renewable generators) and largely ignoring the use of intelligent devices. On the contrary, scientific literature and practice have demonstrated that the wider use of IoT sensors, as well as distributed and remote intelligence, is fundamental to optimize energy consumption. This research work aimed to identify issues due the application of cognitive solutions during the renovation phase of buildings. In particular, the paper presents a cognitive architecture to support the operation and management phases of buildings, thanks to the massive digitalization of the entire supply chain of the construction sector from the single building element to the entire construction process. Such an architecture is capable of combining data from the IoT sensors and actuators of smart objects installed during the renovation phase, as well as legacy building automation systems. As an indication of the capability of the proposed solution, an intelligent window device was developed and validated. Within the Energy, Life Styled, and Seismic Innovation for Regenerated Buildings (ELISIR) project, window units are equipped with sensors to monitor indoor and outdoor condition behaviours of users. In addition, windows are able to react to changes in the environment by means of actuators that enable motorized opening and shading. Thanks to the cognitive layer designed in the project, the window is able to automatically define the best rules for opening and shading by using the local controller to satisfy user’s habits and energy efficiency targets. The cognitive layer defines the appropriate rules for opening and shading using the decision tree algorithm applied to the data generated by the sensors in order to infer users’ preferences. For this research, two prototypes of the window units were installed in two offices of Politecnico di Milano, Italy. The accuracy of this algorithm to classify the users’ behaviour and preferences was found to be around 90%, considering an observation interval of two months.

Low‐frequency 3D synthetic aperture radar for the remote intelligence of building interiors

Low-frequency (LF) synthetic aperture radar (SAR) images offer a viable approach to determining the architecture and contents of buildings and underground bunkers via remote sensing. Often however, standard 2D SAR images can be difficult to interpret due to component signatures from different heights being projected into the scene leading to confused results. In this research, measurement results have shown that the full Nyquist 2D aperture scan approach to 3D through-wall LF SAR provides focussed 3D resolution of a wall and contents behind it in a number of frequency bands. Full-scale radar system upgrades are ongoing in order to investigate numerous other scenarios, however in the meantime, sparse 2D aperture scanning investigations have been undertaken with a prototype radar scanner. Whilst this kind of collection cannot achieve the low sidelobe levels of full Nyquist 2D aperture collections, these prototype scanner measurements are much faster to collect, and have shown encouraging results of sufficient image quality to determine the 3D configuration of prominent features in the target scene, albeit with higher sidelobe or image artefact levels.

Automated stationary human target detector for 3D through‐wall radar imagery

The use of through-wall radar imagery for remote intelligence of building interiors is promising but challenging. Relevant information about human targets and room layout features is typically buried in clutter. In this Letter, the authors propose a methodology for automated extraction of information about stationary human targets behind walls. Based on treatment of the individual blobs found in the imagery, the method consists of thresholding, segmentation, classification and 3D visualisation. Although further optimisation of each of the steps is required, they demonstrate with two examples, including one cluttered scene, that the combination of these steps is effective at eliminating large amounts of clutter and identifying human targets behind walls.

Forward scatter radar for remote intelligence of building interiors

Through-wall radar allows for remote intelligence of building interiors including stand-off detection and tracking of persons inside a building. However, reliable radar tracking of people inside a building is not trivial. Conventional, monostatic through-wall radar measures the backscatter of moving people. The backscatter from a human is relatively low compared with the scattering from building features or furniture. The forward scatter radar (FSR) concept is proposed to detect and possibly track moving people in specific areas of a building. The FSR concept exploits the forward scatter (FS) of objects, which is typically larger than their backscatter; for humans a factor of 20 is possible. It is shown that stand-off detection of moving people inside a building can be performed reliably and consistently based on their FS.

Measurements for remote identification of electrical equipment

The phenomenology of electrical signatures being unintentionally injected onto the mains electricity supply by a range of common household devices is investigated. Measurements were made of both current time series and voltage spectra of a variety of devices, using commercially available measurement equipment designed for electromagnetic compatibility testing. The measurements give strong evidence that multiple devices can be identified from either their current transient when switched on or off, or their voltage spectrum when running. While some devices are readily identifiable, even in the presence of large amounts of noise, for low power devices it may be necessary to perform filtering of the mains signal to obtain spectra with a suitable signal-to-noise ratio. For certain types of device, spectral signatures of particular instances of the same device appear to be separable in high signal-to-noise ratio environments. For example, it may be possible to identify a specific laptop charger among other chargers of the same make and model. The relevant measurements can be made outside buildings, and when combined with other intelligence, could be used to obtain remote intelligence of building interiors.

Situation awareness via Internet of things and in-network data processing

Computing on the edge of the Internet of things comprises among other tasks in-sensor signal processing and performing distributed data fusion and aggregation at network nodes. This poses a challenge to distributed sensor networks of low computing power devices that have to do complex fusion, aggregation and signal processing in situ. One of the difficulties lies in ensuring validity of data collected from heterogeneous sources. Ensuring data validity, for example, the temporal and spatial correctness of data, is crucial for correct in-network data fusion and aggregation. The article considers wireless sensor technology in military domain with the aim of improving situation awareness for military operations. Requirements for contemporary intelligence, surveillance and reconnaissance applications are explored and an experimental wireless sensor network, designed to enhance situation awareness to both in-the-field units and remote intelligence operatives, is described. The sensor nodes have the capability to perform in-sensor signal processing and distributed in-network data aggregation and fusion complying with edge computing paradigm. In-network data processing is supported by service-oriented middleware which facilitates run-time sensor discovery and tasking and ad hoc (re)configuration of the network links. The article describes two experiments demonstrating the ability of the wireless sensor network to meet intelligence, surveillance and reconnaissance requirements. The efficiency of distributed data fusion is evaluated and the importance and effect of establishing data validity is shown.

The Call of the Anthropocene

In late 2012 a communications satellite called EchoStar XVI launched into space from Kazakhstan where it remains in a geostationary orbit around Earth. The satellite contains artist and geographer Trevor Paglen’s The Last Pictures, a collection of one hundred images, sourced from libraries and artists, microetched onto a gold-plated disc. Paglen’s project is both a continuation of, and a critical response to, the notion of the time capsule as a means of delivering, either to a terrestrial future or to some extraterrestrial destination, an abbreviated representative sample of “civilization.” The utopianism that motivates many time-capsule projects, whether it is articulated through a belief in the power to communicate with a distant future or with some cosmically remote intelligence, is also a manifestation, this article argues, of progressive modernity’s commitment to timekeeping—to the successful capture and command, interpretation and anticipation, of past and future times. Paglen’s project is considered here as a retort to the repressions and exclusions that underwrite the optimism of the conventional capsule; The Last Pictures is the futureless call of the Anthropocene.

Impact of Instructional Strategies on Motivation and Engagement for Simulation-Based Training of Robot-Aided ISR Tasks

The U.S. Army projects a considerable increase in the number of operational Unmanned Ground Systems (UGS) within the next ten years. There is a need to enhance UGS capabilities to support remote Intelligence, Surveillance, Reconnaissance (ISR) operations involving the identification of High-Value Individuals (HVI). Emerging UGS capability requirements will inevitably result in new or revised training requirements. The U.S. Army identifies Simulation-Based Training (SBT) as a required training platform for robot-aided ISR tasks utilizing UGSs. In order to implement an effective SBT system, there are several factors to consider related to training systems design and trainee needs. Factors addressed in this study include the selection of effective SBT instructional strategies and the impact on trainee motivation and engagement. Results from this study contribute to design and future research recommendations regarding SBT for robot-aided ISR tasks.

The Remote Intelligence Supervisory System of Heat-Exchanging Station Design and Implementation

The paper come up with a design method about remote and intelligent monitoring system of heat-exchanging station, It adopted fuzzy controller to compute the given temperature of secondary water supply, and used fuzzy PID controller to regulate the valves opening degree, two controllers were built in Matlab software Fuzzy Logic Toolbox, the system adopted Profibus-DP to communicate, and used WinCC configuration software and GPRS communication module to supervise the main parameters of heat-exchanging station, the parameters included temperature and pressure of the secondary water supply. This design enhances intelligentized level and real-time control. And the design also can provide technical support for the similar system.

Recent Patents on Oil Analysis Technologies of Mechanical Equipment

Mechanical equipment condition monitoring and fault diagnosis techniques generally contain vibration signal, sound signal, temperature signal detection and lubricating oil analysis. Oil analysis provides a nondestructive testing diagnostic method for predicting possible impending failure and for avoiding catastrophic failures long before they occur and furthermore tends to determine the frequencies of oil changes and the remaining life of oil with the consequence of reducing maintenance costs and downtime. Oil analysis can be sorted into two categories, namely physical and chemical analysis and WDA analysis. An overview of various normal oil analysis technologies has been addressed. Some real cases resolving engineering problems with oil analysis technology are presented in this review. Fifty one various recent patents were reviewed in this paper on oil analysis technologies and the latent technology developments of oil analysis over the past decade were stated here. Those to some extent show evolution trends concerning latent oil analysis technology and expect future developments in this domain which is on-line and web-based remote intelligence oil analysis monitoring system and information fusion technology.

The human‐centered cyberinfrastructure for scientific and engineering grid applications

This paper illustrates a human‐centered cyberinfrastructure (CI) for conducting scientific and engineering grid applications. CI comprises computing systems, data, information resources, networking, digitally enabled‐sensors, instruments, observatories, and virtual organizations, along with an interoperable suite of software services and tools. The Taiwan Knowledge Innovation National Grid (KING) began with a human‐centered, application‐driven CI. In addition to the development of usual CI which covers the planning of required resources, technology development and forming the environment for research and education, our CI emphasizes how to connect experts and communities via collaborative technologies to work as a virtual organization. The approach technologically leads to bridging and balance between intensive computing which is the base of CI, and pervasive computing which allows a wide variety of access to remote and local intelligence. In applications, topics strongly related to people's living in Taiwan, such as epidemics alleviation support, medical care, flood mitigation and ecological conservation, are of interest and used to drive the CI development. It enables human‐life related applications as a result. The accomplishments and social impacts associated with the applications are highlighted in this article. The Grid middleware and core technologies utilized by individual applications and impacts are also explored in this paper. It is found that pervasive computing technology plays a significant role in human‐life related grid applications, and the demand for data grid support to applications is more than within the intensive computing category. With the accumulated capability, the human‐centered CI can be extended to serve business and industry, and further developed to play a key position in the Asia Pacific cyber‐education and research collaboration.

Networking and Fusion of Disparate Acoustic Sensors for Battlespace Applications

A network of distributed acoustic sensor systems on the ground and/or in the air can be used effectively for autonomous and remote intelligence, surveillance, and reconnaissance (ISR) applications. However interoperability of disparate sensor systems is a major challenge for current coalition force applications. Specifically, a network of acoustic sensor nodes can exhibit heterogeneity in a variety of dimensions. At the sensor‐level, the acoustic sensors can vary in their types (e.g., cardioid vs. omni‐direction) and in their responsiveness to transient and continuous sources. At the node‐level, the acoustic systems can vary in their array configuration, platform mobility, node reactiveness (e.g., timeliness of response), and information processing and output. At the network‐level, the acoustic systems can vary in their communication protocols and access mediums. Current R&D efforts within the US‐UK International Technology Alliance seek to develop a "sensor fabric" technology to seamlessly connect disparate systems for networked sensing applications. Results from a recent field experiment to detect and locate moving ground targets, weapon firings, and explosions via a network of disparate acoustic sensor systems and sensing platforms (e.g., PDA's, workstations, motes and unattended ground sensor systems) are presented.