Successful Deployment Research Articles

Overview of solar thermal technology development and applications in West Africa: Focus on hot water and its applications

Solar thermal technologies can help alleviate the sustainable energy access challenge in West Africa by offering complimentary solutions to reduce dependency on wood and fossil fuels. This paper provides a comprehensive regional overview of the water-based solar heating technology sector in West Africa in order to identify crucial factors that could boost a successful deployment of solar water heating systems in the region. Emphasis is placed on solar water heaters (SWHs), solar sorption refrigeration and solar heat for industrial process. The article summarizes the salient characteristics of widely used technological solutions and offers an understanding of the development and applications of solar water heating technology in the region. The review includes trends and research focusing on market, technologies, local manufacturing and policies, and shows that solar water heating potential remains scarcely exploited, with different status in different countries in the region. There are mostly thermosiphon systems with very few pumped systems. Industrial applications are practically inexistent, including concentrated solar heat. Finally, problems lying in the solar thermal sector in West Africa are analysed and measures for solving the problems are suggested.

Decision-making tree for optimal Woven EndoBridge device sizing with ideal Woven EndoBridge-aneurysm volume (iWAVe) ratio

PurposeOptimal size selection is important for successful Woven EndoBridge (WEB) treatment. Conventional recommendations for WEB sizing based on aneurysm width and height sometimes require device exchange. We aimed to design a novel volume-based parameter, the ideal WEB-aneurysm volume (iWAVe) ratio, for optimal WEB sizing. MethodsConsecutive patients who underwent WEB treatment for wide-neck bifurcation aneurysms between January 2021 and May 2022 were retrospectively reviewed. Aneurysm volume was automatically calculated using software. We measured the aneurysm volume based on the expected position of the device within the aneurysm. The WAVe ratio was defined as the ratio of the aneurysm volume to WEB volume. We dichotomized aneurysms treated with a successful sizing or unsuccessful sizing for WEB (successful group and unsuccessful group, respectively). ResultsThirty-five patients were eligible for study enrollment. Ten patients (28.6%) needed to exchange the WEB on the first attempt and required another WEB on the second attempt resulting in deployment success. Hence, 35 aneurysms were in the successful group and 10 were in the unsuccessful group. The median WAVe ratio was 1.0 (range 0.76–1.31) in the successful group and 1.27 (0.58–1.89) in the unsuccessful group. Using logistic regression, iWAVe ratio was from 0.90–1.16 to secure a >80% probability of success by the 95% lower confidence limit. The sensitivity and specificity of the iWAVe ratio for optimal size selection on the first attempt were 0.60 and 1.00, respectively. ConclusionDecision-making based on aneurysm width and the iWAVe ratio could promote optimal WEB sizing.

Endovascular Treatment of Chronic Post-Dissection Thoraco-Abdominal Aneurysms Using Inner Branch Device (Ibevar): A Preliminary Single Center Experience

Abstract Background Although open surgery remains the gold standard for the treatment of post-dissection thoraco-abdominal aneurysms (TAAAs), the endovascular approach using fenestrated or branched endografts has emerged as a valid alternative for patients considered at high risk for surgery. The use of inner branch devices (iBEVAR) combining benefits of fenestrations and outer branches could offer an ideal configuration in this context. Aims Our aim was to report our preliminary monocentric experience with iBEVAR in the treatment of post-dissection TAAAs. Methods A retrospective analysis of prospective data retrieved from 1 center between Mars 2020 and January 2023 was done. Endpoints were immediate technical success, postoperative morbidity, rate of endoleaks, re-intervention and mortality. Results During this period, 18 patients (mean age 66,5 years, range 41-80) were identified. All were asymptomatic and operated in a 2-steps procedure with a TEVAR first. There were 5 off-the-shelf E-nside (28%) and 13 custom-made Extra-Design grafts (72%). Despite successful endograft deployment in all patients and branch catheterization in 68/70 cases (97%), the technical success was 94% due to an open conversion for ilio-mesenteric bypass. The 30-days mortality was 0%. During the post-operative period, 17% of patients (3/18) presented complications with 1 case of mesenteric ischaemia requiring a visceral resection and 2 cases of paralytic ileus, treated conservatively. No spinal cord ischemia was observed. During the median follow-up of 16 months (range 1-36), 4 patients (22%) had a re-intervention: one case of type-Ic endoleak treated with an additional renal stent and 3 cases of type-III endoleaks in the celiac trunk requiring a relining. The overall target vessel patency was 100%. In all cases, the sac diameter remained stable. Conclusions The use of iBEVAR appears to be safe and effective for the treatment of post-dissection TAAAs with an acceptable rate of complications. Further patients and longer follow-up are needed.

Reliability of autonomous solar-wind microgrids with battery energy storage system applied in the residential sector

Residential electricity generation can benefit from the successful deployment of photovoltaic (PV) and wind renewable energy sources. However, their intermittent nature poses a significant limitation. To address this, a hybrid system can be employed to enhance system reliability and efficiency. Reliability analysis plays a crucial role in evaluating the energy production capacity to meet the demand. This study aims to assess the reliability of a hybrid PV/wind microgrid through simulation. Data from a residence were collected every 10 s, and average values were computed on an hourly basis and exported for computer processing. Solar irradiation, wind speed, and temperature data were also utilized. The modeling process involved defining the PV panel, wind turbines, battery energy storage system (BESS), management strategy, and energy autonomy. The results indicate that when PV and wind systems operate independently, they are unable to consistently reduce the residential energy deficit. However, the PV/Wind/BESS configuration significantly improves system operation and proves sufficient to meet the required load in most hours. Through this configuration, only 42.5% of the total PV/wind energy utilized by the residents needs to be dispatched through the BESS. Moreover, the BESS capacity is reduced by 50% when the systems are used separately. The public grid only supplies power when the BESS is insufficient to cover the load. Therefore, the optimal sizing of the BESS plays a critical role in system viability, reducing initial installation costs, regulating microgrid parameters, and contributing to the reduction of the energy deficit. Hence, investigating the fundamental design parameters of the microgrid and BESS is essential for identifying the optimal capacity of the system and ensuring model reliability.

Computational modeling of DLBCL predicts response to BH3-mimetics

In healthy cells, pro- and anti-apoptotic BCL2 family and BH3-only proteins are expressed in a delicate equilibrium. In contrast, this homeostasis is frequently perturbed in cancer cells due to the overexpression of anti-apoptotic BCL2 family proteins. Variability in the expression and sequestration of these proteins in Diffuse Large B cell Lymphoma (DLBCL) likely contributes to variability in response to BH3-mimetics. Successful deployment of BH3-mimetics in DLBCL requires reliable predictions of which lymphoma cells will respond. Here we show that a computational systems biology approach enables accurate prediction of the sensitivity of DLBCL cells to BH3-mimetics. We found that fractional killing of DLBCL, can be explained by cell-to-cell variability in the molecular abundances of signaling proteins. Importantly, by combining protein interaction data with a knowledge of genetic lesions in DLBCL cells, our in silico models accurately predict in vitro response to BH3-mimetics. Furthermore, through virtual DLBCL cells we predict synergistic combinations of BH3-mimetics, which we then experimentally validated. These results show that computational systems biology models of apoptotic signaling, when constrained by experimental data, can facilitate the rational assignment of efficacious targeted inhibitors in B cell malignancies, paving the way for development of more personalized approaches to treatment.

Quality changes in workplace health promotion over time: an extended validation of quality criteria from a longitudinal perspective

AimThe quality of workplace health promotion (WHP) is essential for the successful deployment of financial and human resources. The aim of this paper is to evaluate the measurement quality of a WHP instrument with 15 quality criteria over time. In addition, it examines whether the quality of WHP in the enterprises concerned changed over time and whether typical developments can be identified. Finally, the role of company parameters such as size and implementation phase are analysed in relation to how WHP develops over time.Subjects and methodsEvaluations of the quality of WHP collected between 2014 and 2021 were available at two and three measurement points for 570 and 279 enterprises, respectively. To assess the longitudinal measurement structure, confirmatory factor analyses were carried out followed by structural equation modelling to analyse causality. Cluster analysis was used to identify typical developments, and differences in company parameters were analysed with MANOVA.ResultsThe results prove that the 15 quality criteria can be used to evaluate the quality of WHP in enterprises in a valid and reliable manner, both cross-sectionally and longitudinally. The quality of WHP in the enterprises concerned remained relatively stable over approximately 12 years. The cluster solution revealed three different developments characterized by increasing, stable or decreasing quality.ConclusionMeasurements using a quality evaluation system permit a good assessment of WHP in enterprises. WHP quality also depends on company parameters; here more support should be provided to motivate enterprises in the long run, particularly in the sustainability phase.

Securing AMI-IoT networks against multiple RPL attacks using ensemble learning IDS and light-chain based prediction detection and mitigation mechanisms

ABSTRACT Advanced Metering Infrastructure (AMI) is one of the Internet of Things (IoT) enabled smart applications of smart grids. The Routing Protocol for Low Power and Lossy network (RPL) has been accepted to facilitate effective routing services for the AMI. However, numerous RPL attacks appear in AMI due to resource scarcity and dubious wireless medium, which significantly impedes the successful deployment of AMI-RPL. To enable secure and reliable AMI-RPL, this work proposes a novel Intrusion Detection System (IDS) named AMI Attack-aware Intelligent Machine learning IDS (AIMS). The primary objectives of AIMS are to predict, detect, and mitigate different types of RPL security attacks in the AMI environment. To predict the RPL attacks using the Stacked Ensemble (SE) machine learning model, a novel AMI-RPL Attack Dataset (ARAD) is generated by the Cooja simulator with the suitable pre-processing and the Spider Monkey Optimization (SMO) based feature selection. The advanced prediction of attack nodes improves the performance and significantly diminishes the future damages of AMI. The attack detection is based on immutable blocks of a light-chain model, and the cryptocurrency-based mitigation model effectively isolates the attackers. AIMS mechanism amplifies RPL security with high reliability and maximizes the AMI network lifetime by delivering superior results.

Fluxbots: A Method for Building, Deploying, Collecting and Analyzing Data From an Array of Inexpensive, Autonomous Soil Carbon Flux Chambers

AbstractSoil carbon flux rates are a crucial metric of carbon cycling that contribute to calculating an ecosystem's carbon budget, and thus whether it is a source or sink of atmospheric carbon dioxide. However, soil carbon flux datasets are frequently low‐resolution across either space or time, limiting our abilities to identify small‐scale ecological contexts that influence soil carbon dynamics. Existing datasets are distributed unevenly, with some soil carbon‐rich regions (like tropical grasslands) significantly understudied. We developed an autonomous, inexpensive, do‐it‐yourself (DIY) soil carbon flux chamber (a “fluxbot”) and data processing software. We deployed a distributed array of 12 fluxbots in a long‐term experiment in a central Kenyan savanna where it has been logistically impossible to collect high‐resolution soil carbon flux data. With this array we collected over 10,000 individual flux estimates over almost two months, spanning the end of a dry season and the start of a wet season. With our successful deployment in situ, we demonstrate the potential for low‐cost, autonomous, DIY sensors in improving resolution of soil carbon flux datasets (particularly in under‐studied or logistically challenging systems). If implemented widely, such an improvement in data collection capacities could improve our understanding of ecological and climatic drivers of soil carbon flux dynamics on the local to global scale.

Impact of Preprocedure Imaging for Left Atrial Appendage Occlusion: Insights From the NCDR LAAO Registry

BackgroundThe impact of preprocedure imaging on the safety and effectiveness of left atrial appendage occlusion (LAAO) remains unclear. ObjectivesThis study sought to determine the rates of use of preprocedure computed tomography (CT)/cardiac magnetic resonance (CMR) and its association with safety and effectiveness of LAAO procedures. MethodsThe National Cardiovascular Data Registry LAAO Registry was used to evaluate patients who underwent attempted LAAO with the WATCHMAN and WATCHMAN FLX devices between January 1, 2016, and June 30, 2021. Safety and effectiveness of LAAO procedures was compared by use vs nonuse of preprocedural CT/CMR. Outcomes of interest included implantation success (deployment and release of device), device success (device released with peridevice leak <5 mm), and procedure success (device released with peridevice leak <5 mm and no in-hospital major adverse events [MAE]). Multivariable logistic regression was used to assess the relationship between preprocedure imaging and outcomes. ResultsPreprocedure CT/CMR was used for 18.2% (n = 20,851) of the 114,384 procedures in this study. CT/CMR use was more common among government and university hospitals and hospitals in the Midwest and South; it was less common among patients with uncontrolled hypertension, with abnormal renal function, and without prior thromboembolism. Overall rates of implantation success, device success, and procedure success were 93.4%, 91.2%, and 89.4%, respectively. Preprocedure CT/CMR was independently associated with an increased likelihood of implantation success (OR: 1.08; 95% CI: 1.00-1.17), device success (OR: 1.10; 95% CI: 1.04-1.16), and procedural success (OR: 1.07; 95% CI: 1.02-1.13). MAE were uncommon (2.3%) and not associated with use of preprocedure CT/CMR (OR: 1.02; 95% CI: 0.92-1.12). ConclusionsPreprocedure CT/CMR was associated with an increased likelihood of successful LAAO implantation; however, the magnitude of benefit appears small and it was not associated with MAE.

Nano to macro-mechanical properties of laser directed energy deposited CoCrNi medium entropy alloy

The CoCrNi Medium Entropy Alloy is a popular subset of the Cantor alloy due to its superior cryogenic and elevated temperature properties. This study reports the successful deployment of a laser-based near-net shaping technique known as laser directed energy deposition (LDED) to fabricate the CoCrNi MEA. The effect of laser power and scan speed on track geometry is studied in detail. The bulk deposition is performed using a parametric combination yielding regular defect-free tracks with an aspect ratio greater than five and a maximum deposition rate. The EBSD analysis revealed a strong < 001 > cubic texture along the build direction, due to the thermal gradient in that direction. Across both the scan and build directions, the cellular and columnar substructure is observed. Solid solution strengthening and dislocation strengthening contribute 39 % and 42 % to yield strength. The nanoindentation analysis revealed hardness, reduced modulus, and elastic modulus of 6.32 ± 0.32 GPa, 222.08 ± 5.72 GPa, and 250.62 ± 8.25 GPa, respectively. The contact stiffness, reduced modulus, and hardness showed a positive linear relationship with strain rate. The strain rate sensitivity of MEA is in the range of 0.030–0.042, which is higher than that of conventional fcc metals. It is attributed to the higher lattice frictional stresses and different atomic-level structures of MEA than conventional fcc metals. Furthermore, chemical short-range ordering and a stronger peierls barrier resulted in a lower activation volume of the order of ∼100b3. The present study provides a detailed understanding of the effect of process parameters on melt-pool geometry, microstructure evolution, as well as the influence of strain rate on nanomechanical properties.

Initial experience with a modified "candy-plug" technique for false lumen embolization in chronic type B aortic dissection.

Persistent distal false lumen (FL) perfusion after thoracic endovascular aortic repair (TEVAR) for type B aortic dissection (TBAD) can lead to aneurysmal degeneration and an increased risk of rupture. We have presented our initial experience using a modified "candy-plug" (CP) technique for FL embolization. From February 2021 to July 2022, we treated six patients using the modified CP technique. All the patients had undergone prior or simultaneous TEVAR for chronic TBAD with persistent FL perfusion and aneurysm expansion. Bilateral common femoral artery access was obtained, and intravascular ultrasound was used to confirm wire access in the true lumen (TL) and FL. A conformable TAG device (W.L. Gore & Associates, Flagstaff, AZ) was used in four cases and an Excluder aortic cuff (W.L. Gore & Associates) in two cases. The device was modified by placing a constraining "napkin-ring" suture through the middle segment of the device. Femoral sheaths were placed in the TL and FL. A standard TL TEVAR extension was performed at the level of the celiac artery (zone 5). Next, the CP device was advanced and deployed in the FL, distally aligning it with the TL device. An appropriately sized Amplatzer II plug (Abbot Vascular, Santa Clara, CA) was then deployed in the constrained segment of the modified stent graft. Completion angiography was performed to confirm successful FL embolization. Technical success was defined as successful deployment of the CP device in the FL. The technical success rate was 100% (six of six patients). Clinical success was defined as the cessation of aneurysm growth on follow-up computed tomography angiography. No 30-day mortality, myocardial infarction, stroke, spinal cord ischemia, access site complications, or aortic-related reinterventions occurred. Surveillance imaging at a mean follow-up of 10months confirmed clinical success (stable aneurysm size or shrinkage) for all five patients with follow-up data available. The modified CP embolization technique is a promising solution for persistent distal FL perfusion after TEVAR for TBAD. Further investigation is required to determine the long-term durability of this technique as an adjunct to TEVAR to promote aortic remodeling.

Editorial: Toyota Production System practices asFast‐and‐Frugalheuristics

Editorial: Toyota Production System practices as<scp>Fast‐and‐Frugal</scp>heuristics

Successful deployment of an Artificial Intelligence solution for primary diagnosis of prostate biopsies in clinical practice

In order to evaluate the feasibility of artificial intelligence within the setting of prostate histopathology, 3975 slides from 860 patients were digitally scanned and supplied to the IBEX-Artificial Intelligence (AI) system before evaluation by histopathology consultants with recommendations from the AI. Data comparing reporting with and without AI assistance were analysed along with accuracy of diagnosis for the AI. Request rates for additional immunohistochemistry from consultants in cases of diagnostic uncertainty dropped from 8.7 % to 4.5 %. Qualitative reporting confidence increased with AI assistance and valued the highlighting of the most suspicious areas within a biopsy. Positive and negative predictive values for the AI were 0.994 and 0.995 when using the consultants’ diagnosis as the true value. AI shows significant potential as an assistant for histopathologists in the field of cancer diagnosis.

P128 Successful deployment of a cystic fibrosis registry solution in a low-and-middle-income country – a pilot

In many patient registries of lower-and middle-income countries (LMIC), information is scarce, and little CF outcome data is accessible at the center level. Current barriers to effective data management include cumbersome design and user interface, limited infrastructure and time for data entry, inconsistent field definitions, incomplete datasets, and lack of resources to develop and implement solutions. These factors prevent adoption, use, and sustainability of LMIC registries. We saw the need for a practical approach, and here report the successful pilot of a patient management and registry tool using a standard platform.

Nitric Oxide Regulates the Ralstonia solanacearum Type III Secretion System.

Ralstonia solancearum causes bacterial wilt disease on diverse plant hosts. R. solanacearum cells enter a host from soil or infested water through the roots, then multiply and spread in the water-transporting xylem vessels. Despite the low nutrient content of xylem sap, R. solanacearum grows very well inside the host, using denitrification to respire in this hypoxic environment. R. solanacearum growth in planta also depends on the successful deployment of protein effectors into host cells via a type III secretion system (T3SS). The T3SS is absolutely required for R. solanacearum virulence, but it is metabolically costly and can trigger host defenses. Thus, the pathogen's success depends on optimized regulation of the T3SS. We found that a byproduct of denitrification, the toxic free-radical nitric oxide (NO), positively regulates the R. solanacearum T3SS both in vitro and in planta. Using chemical treatments and R. solanacearum mutants with altered NO levels, we show that the expression of a key T3SS regulator, hrpB, is induced by NO in culture. Analyzing the transcriptome of R. solanacearum responding to varying levels of NO both in culture and in planta revealed that the T3SS and effectors were broadly upregulated with increasing levels of NO. This regulation was specific to the T3SS and was not shared by other stressors. Our results suggest that R. solanacearum may experience an NO-rich environment in the plant host and that this NO contributes to the activation of the T3SS during infection. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Robotic process automation deployments: a step-by-step method to investment appraisal

PurposeRobotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.Design/methodology/approachThe methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.FindingsThe step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.Practical implicationsBy following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.Originality/valueThe paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

In companies we trust: consumer adoption of artificial intelligence services and the role of trust in companies and AI autonomy

PurposeCompanies utilize increasingly capable Artificial Intelligence (AI) technologies to deliver modern services across a range of consumer service industries. AI autonomy, however, sparks skepticism among consumers leading to a decrease in their willingness to adopt AI services. This raises the question as to whether consumer trust in companies can overcome consumer reluctance in their decisions to adopt high (vs low) autonomy AI services.Design/methodology/approachUsing a representative survey (N = 503 consumers corresponding to N = 3,690 observations), this article investigated the link between consumer trust in a company and consumers' intentions to adopt high (vs low) autonomy AI services from the company across 23 consumer service companies accounting for six distinct service industries.FindingsThe results confirm a significant and positive relationship between consumer trust in a company and consumers' intentions to adopt AI services from the same company. AI autonomy, however, moderates this relationship, such that high (vs low) AI autonomy weakens the positive link between trust in a company and AI service adoption. This finding replicates across all 23 companies and the associated six industries and is robust to the inclusion of several theoretically important control variables.Originality/valueThe current research contributes to the recent stream of AI research by drawing attention to the interplay between trust in companies and adoption of high autonomy AI services, with implications for the successful deployment and marketing of AI services.

Responsive FLEXibility: A smart local energy system

The transition towards a more decarbonised, resilient and distributed energy system requires local initiatives, such as Smart Local Energy Systems (SLES), which lead communities to gain self-sufficiency and become electricity islands. Although many SLES projects have been recently deployed, only a few of them have managed to be successful, mostly due to an initial knowledge gap in the SLES planning and deployment phases. This paper leverages the knowledge from the UK’s largest SLES demonstrator in the Orkney Islands, named the Responsive FLEXibility (ReFLEX) project, to propose a framework that will help communities to successfully implement a SLES. First, this paper describes how the multi-services electrical SLES implemented in Orkney reduces the impact of the energy transition on the electrical infrastructure. We identify and discuss the main enablers and barriers to a successful SLES, based on a review of SLES projects in the UK. Second, to help future communities to implement SLES, we extend the Smart Grid Architecture Model (SGAM) into a comprehensive multi-vector Smart Local Energy Architecture Model (SLEAM) that includes all main energy services, namely power, heat and transport. This extended architecture model describes the main components and interaction layers that need to be addressed in a comprehensive SLES. Next, to inform successful deployment of SLES, an extensive list of key performance indicators for SLES is proposed and implemented for the ReFLEX project. Finally, we discuss lessons learnt from the ReFLEX project and we list required future technologies that enable communities, energy policy makers and regulatory bodies to best prepare for the energy transition.

MGFNet: A Progressive Multi-Granularity Learning Strategy-Based Insulator Defect Recognition Algorithm for UAV Images

Due to the low efficiency and safety of a manual insulator inspection, research on intelligent insulator inspections has gained wide attention. However, most existing defect recognition methods extract abstract features of the entire image directly by convolutional neural networks (CNNs), which lack multi-granularity feature information, rendering the network insensitive to small defects. To address this problem, we propose a multi-granularity fusion network (MGFNet) to diagnose the health status of the insulator. An MGFNet includes a traversal clipping module (TC), progressive multi-granularity learning strategy (PMGL), and region relationship attention module (RRA). A TC effectively resolves the issue of distortion in insulator images and can provide a more detailed diagnosis for the local areas of insulators. A PMGL acquires the multi-granularity features of insulators and combines them to produce more resilient features. An RRA utilizes non-local interactions to better learn the difference between normal features and defect features. To eliminate the interference of the UAV images’ background, an MGFNet can be flexibly combined with object detection algorithms to form a two-stage object detection algorithm, which can accurately identify insulator defects in UAV images. The experimental results show that an MGFNet achieves 91.27% accuracy, outperforming other advanced methods. Furthermore, the successful deployment on a drone platform has enabled the real-time diagnosis of insulators, further confirming the practical applications value of an MGFNet.

Digital Health Inclusion: A Pilot Study of Health Services Deployment Using Communications Satellite for the Underserved in Nigeria

Health service delivery in Nigeria is constrained by: brain drain, insufficient infrastructure and technology, poor and inadequate medical facilities and paucity of medical specialists in rural and remote regions - thus leading to a high rate of “medical tourism”. With increasing mobile phone ownership in Nigeria, mobile technology-based telemedicine has the potential to improve Nigeria’s healthcare delivery with enabling infrastructural facilities. In this paper, a pilot study that uses Nigeria’s communication satellite system for virtual Telemedicine connection between health practitioners and underserved communities using the “one2one” mobile telemedicine application is reported. This pilot study aimed to deploy Nigeria’s communication satellite system to enable virtual telemedicine connection between health practitioners and underserved communities using the “one2one” mobile telemedicine app. Successful deployment of a 1.8m VSAT dish at the pilot clinic and testing showed robust internet connectivity with a time delay of 250ms per hop. Furthermore, the One2one app was successfully installed on health practitioners’ tablets/phone and patients’ phone/tablets. Over 100 patients were treated using the one2one app connected through the satellite internet. The one2one app was highly rated by patients and healthcare providers in terms of usability with the highest score being ease of use 87%. This study shows that Nigeria’s communications satellite can be deployed to support mobile telemedicine as part of the effort to increase access to doctors and specialists in medically underserved areas of Nigeria.