Search results for: Hamda M. Al-Ali

Authors: Imil Hamda Imran, Sami El Ferik

Abstract:

This paper deals with adaptive cooperative control of non holonomic mobile robot moved together in a given formation. The controller is designed based on the Immersion and Invariance (I&I) approach. I&I is a framework for adaptive stabilization of nonlinear systems with uncertain parameters. We investigate the tracking control of non holonomic mobile robot with uncertainties in The I&I-based adaptive controller regulates the angular and linear velocity of non holonomic mobile robot. The results demonstrate that the ability of I&I-based adaptive cooperative control in tracking the position of non holonomic mobile robot.

Keywords: nonholonomic mobile robot, immersion and invariance, adaptive control, uncertain nonlinear systems

Procedia PDF Downloads 497

Authors: Mohammad Ali Al-Deeb, Hamda Ateeq Al Dhaheri

Abstract:

Insects cause major damage to crops and fruit trees worldwide. In the United Arab Emirates, the date palm tree is the most economically important tree which is used for date production as well as an ornamental tree. In 2002, the number of date palm trees in UAE was 40,700,000 and it is increasing over time. The longhorn stem borer (Jebusaea hammerschmidtii) and the lesser date month (Batrachedra amydraula) are important insect pests causing damage to date palm trees in UAE. Population dynamics of the Jebusaea hammerschmidtii and Batrachedra amydraula were studied by using light and pheromons traps, respectively in Al-Ain, UAE. The first trap catch of B. amydraula adults occurred on 19 April and the insect population peaked up on 26 April 2014. The first trap catch of J. hammerschmidtii occurred in April 2014. The numbers increased over time and the population peak occurred in June. The trapping was also done in 2015. The changes in insect numbers in relation to weather parameters are discussed. Also, the importance of the results on the management of these two pests is highlighted.

Keywords: date palm, integrated pest management, UAE, light trap, pheromone trap

Procedia PDF Downloads 281

Authors: Hissa Sadiq, Abdullah Abu-Tineh, Fatma Al-Mutawah, Hamda Al-Sulaiti

Abstract:

The purpose of this quantitative study was to measure the difference in levels of satisfaction of students, teachers, and parents in schools run by licensed school leaders comparing with schools run by unlicensed school leaders. Data was gathered from 108 school performance reports as published by Ministry of Education and Higher Education for the year 2015-2016. School leaders in 58 participating schools obtained the professional licenses while school leaders in 56 participating schools have no professional licenses. Percentages, standard deviations, and t-tests were used to analyze the data. Results showed that no statistical differences were found in students’ satisfaction between the two school types. However, there were statistical differences in parents and teachers’ satisfaction in the two school types attributed to obtaining the professional license. Teachers and parents of students in schools run by licensed school leaders satisfied more than schools run by unlicensed school leaders. Finally, many recommendations and implications were discussed and proposed. This paper was made possible by NPRP grant # (NPRP7-1224-5-178) from the Qatar national research fund (a member of Qatar Foundation) to Abdullah M. Abu-Tineh. The statements made herein are solely the responsibility of the author

Keywords: professional licenses, Qatari schools, licensure system, satisfaction

Procedia PDF Downloads 207

Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

Abstract:

The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

Procedia PDF Downloads 531

Authors: We'aam Alali, Ziad Saffour, Saker Saloum

Abstract:

Low-pressure, sulfur hexafluoride (SF₆) remote radio-frequency (RF) plasma, ignited in a hollow cathode discharge (HCD-L300) plasma system, has been shown to be a powerful method in cotton fabric finishing to achieve water-repellent property. This plasma was ignited at an SF6 flow rate of (200 cm), low pressure (0.5 mbar), and radio frequency (13.56 MHz) with a power of (300 W). The contact angle has been measured as a function of the plasma exposure period using the water contact angle measuring device (WCA), and the changes in the morphology, chemical structure, and mechanical properties as tensile strength and elongation at the break of the fabric have also been investigated using the scanning electron microscope (SEM), energy-dispersive X-ray spectroscopy (EDX), attenuated total reflectance Fourier transform Infrared spectroscopy (ATR-FTIR), and tensile test device, respectively. In addition, weight loss of the fabric and the fastness of washing have been studied. It was found that the exposure period of the fabric to the plasma is an important parameter. Moreover, a good water-repellent cotton fabric can be obtained by treating it with SF₆ plasma for a short time (1 min) without degrading its mechanical properties. Regarding the modified morphology of the cotton fabric, it was found that grooves were formed on the surface of the fibers after treatment. Chemically, the fluorine atoms were attached to the surface of the fibers.

Keywords: cotton fabric, SEM, SF₆ plasma, water-repellency

Procedia PDF Downloads 79

Authors: Jose G. Tshikuka, Goabaone Rankgoane-Pono, Mgaywa G. M. D. Magafu, Julius C. Mwita, Tiny Masupe, Fortunat M. Kandanda, Shimeles G. Hamda, Roy Tapera, Mooketsi Molefi, John T. Tlhakanelo

Abstract:

Background: Factors associated with overweight and obesity among antiretroviral therapy (ART) recipients have not been sufficiently studied in Botswana. We aimed to study (i) the prevalence and trends in overweight/obesity by duration of exposure to ART among recipients, (ii) changes in body mass index (BMI) categories among recipients before ART initiation (BMI-1) and after ART initiation (BMI-2), (iii) associations between ART and overweight/obesity and (iv) factors associated with BMI changes among ART recipients. Methods: A 12 years retrospective record-based review was conducted. Factors potentially associated with BMI change among patients after at least three years of ART exposure were examined using multiple regression model. Adjusted odds ratios (AOR) and their 95% confidence intervals (CIs) were computed. ART regimens, duration of exposure to ART, and recipients’ demographic and biomedical characteristics including the presence or absence of diabetes mellitus related comorbidities (DRC) were investigated as potential factors associated with overweight/obesity. Results: Twenty-nine percent of recipients were overweight, 16.6% had obesity of whom 2.4% were morbidly-obese at the last clinic visit. Overweight/obesity recipients were more likely to be female, to have DRC and less likely to have nadir CD4 count or CD4 count between 201 – 249 cells/mm³. Neither the first-line nor the second-, third-line ART regimens predicted overweight/obesity more than the other and neither did the duration of exposure to ART. No significant linear trends were observed in the prevalence of overweight/obesity by the duration of exposure to ART. Conclusions: These results indicate that overweight/obesity seen among ART recipients is not directly induced by ART. ART used CD4 and/or DRC pathway to induce overweight/obesity seen among recipients; suggesting that, weight gain documented herein is likely a reflection of improved health status that mirrors trends in the general population or a DRC related effect. Weight management programs may be important components of HIV care.

Keywords: overweight/obesity, recipients of antiretroviral therapy, HIV/AIDS, Botswana

Procedia PDF Downloads 158

Authors: Surah Aldakhl, Dafer Alali, Mohamed Zohdy

Abstract:

The next generation of electricity grid infrastructure, known as the "smart grid," integrates smart ICT (information and communication technology) into existing grids in order to alleviate the drawbacks of existing one-way grid systems. Future power systems' efficiency and dependability are anticipated to significantly increase thanks to the Smart Grid, especially given the desire for renewable energy sources. The security of the Smart Grid's cyber infrastructure is a growing concern, though, as a result of the interconnection of significant power plants through communication networks. Since cyber-attacks can destroy energy data, beginning with personal information leaking from grid members, they can result in serious incidents like huge outages and the destruction of power network infrastructure. We shall thus propose a secure smart energy management system based on the Blockchain as a remedy for this problem. The power transmission and distribution system may undergo a transformation as a result of the inclusion of optical fiber sensors and blockchain technology in smart grids. While optical fiber sensors allow real-time monitoring and management of electrical energy flow, Blockchain offers a secure platform to safeguard the smart grid against cyberattacks and unauthorized access. Additionally, this integration makes it possible to see how energy is produced, distributed, and used in real time, increasing transparency. This strategy has advantages in terms of improved security, efficiency, dependability, and flexibility in energy management. An in-depth analysis of the advantages and drawbacks of combining blockchain technology with optical fiber is provided in this paper.

Keywords: smart grids, blockchain, fiber optic sensor, security

Procedia PDF Downloads 118

Authors: Nabeeha Hassan Abdel Jalil, Robert Barigye, Hamda Al Alawi, Afra Al Dhaheri, Fatma Graiban Al Muhairi, Maryam Al Khateri, Nouf Al Alalawi, Susan Olet, Khaja Mohteshamuddin, Ahmad Al Aiyan, Mohamed Elfatih Hamad

Abstract:

A serological survey was carried out to determine the seroprevalence of Brucella spp, Coxiella burnetii, Chlamydophila abortus, and Toxoplasma gondii in sheep and goat herds in the UAE. A total of 915 blood samples [n= 222, [sheep]; n= 215, [goats]) were collected from livestock farms in the Emirates of Abu Dhabi, Dubai, Sharjah and Ras Al-Khaimah (RAK). An additional 478 samples (n= 244, [sheep]; n= 234, (goats]) were collected from the Al Ain livestock central market and tested by indirect ELISA for pathogen-specific antibodies with the Brucella antibodies being further corroborated by the Rose-Bengal agglutination test. Seropositivity for the four pathogens is variably documented in sheep and goats from the study area. Respectively, the overall livestock farm prevalence rates for Brucella spp, C. burnetii, C. abortus, and T. gondii were 2.7%, 27.9%, 8.1%, and 16.7% for sheep, and 0.0%, 31.6%, 9.3%, and 5.1% for goats. Additionally, the seroprevalence rates Brucella spp, C. burnetii, C. abortus, and T. gondii in samples from the livestock market were 7.4%, 21.7%, 16.4%, and 7.0% for sheep, and 0.9%, 32.5%, 19.2%, and 11.1% for goats respectively. Overall, sheep had 12.59 more chances than goats of testing seropositive for Brucella spp (OR, 12.59 [95% CI 2.96-53.6]) but less likely to be positive for C. burnetii-antibodies (OR, 0.73 [95% CI 0.54-0.97]). Notably, the differences in the seroprevalence rates of C. abortus and T. gondii in sheep and goats were not statistically significant (p > 0.0500). The present data indicate that all the four study pathogens are present in sheep and goat populations in the UAE where coxiellosis is apparently the most seroprevalent followed by chlamydophilosis, toxoplasmosis, and brucellosis. While sheep from the livestock market were more likely than those from farms to be Brucella-seropositive than those, the overall exposure risk of C. burnetii appears to be greater for goats than sheep. As more animals from the livestock market were more likely to be seropositive to Chlamydophila spp, it is possible that under the UAE animal production conditions, at least, coxiellosis and chlamydophilosis are more likely to increase the culling rate of domesticated small ruminants than toxoplasmosis and brucellosis. While anecdotal reports have previously insinuated that brucellosis may be a significant animal health risk in the UAE, the present data suggest C. burnetii, C. abortus and T. gondii to be more significant pathogens of sheep and goats in the country. Despite this possibility, the extent to which these pathogens may nationally be contributing to reproductive failure in sheep and goat herds is not known and needs to be investigated. Potentially, these agents may also carry a potentially zoonotic risk that needs to be investigated in risk groups like farm workers, and slaughter house personnel. An ongoing study is evaluating the seroprevalence of bovine coxiellosis in the Emirate of Abu Dhabi and the data thereof will further elucidate on the broader epidemiological dynamics of the disease in the national herd.

Keywords: Brucella spp, Chlamydophila abortus, goat, sheep, Toxoplasma gondii, UAE

Procedia PDF Downloads 200

Authors: Hamda M. Al-Ali

Abstract:

From addressing fundamental questions about the history of the solar system to exploring other planets for any signs of life have always been the core of human space exploration. This triggered humans to explore whether other planets such as Mars could support human life on them. Therefore, many planned space missions to other planets have been designed and conducted to examine the feasibility of human survival on them. However, space missions are expensive and consume a large number of various resources to be successful. To overcome these problems, material efficiency shall be maximized through the use of reusable launch vehicles (RLV) rather than disposable and expendable ones. Material efficiency is defined as a way to achieve service requirements using fewer materials to reduce CO2 emissions from industrial processes. Materials such as aluminum-lithium alloys, steel, Kevlar, and reinforced carbon-carbon composites used in the manufacturing of spacecrafts could be reused in closed-loop cycles directly or by adding a protective coat. Material efficiency is a fundamental principle of a circular economy. The circular economy aims to cutback waste and reduce pollution through maximizing material efficiency so that businesses can succeed and endure. Five strategies have been proposed to improve material efficiency in the space industry, which includes waste minimization, introduce Key Performance Indicators (KPIs) to measure material efficiency, and introduce policies and legislations to improve material efficiency in the space sector. Another strategy to boost material efficiency is through maximizing resource and energy efficiency through material reusability. Furthermore, the environmental effects associated with the rapid growth in the number of space missions include black carbon emissions that lead to climate change. The levels of emissions must be tracked and tackled to ensure the safe utilization of space in the future. The aim of this research paper is to examine and suggest effective methods used to improve material efficiency in space missions so that space and Earth become more environmentally and economically sustainable. The objectives used to fulfill this aim are to identify the materials used in space missions that are suitable to be reused in closed-loop cycles considering material efficiency indicators and circular economy concepts. An explanation of how spacecraft materials could be re-used as well as propose strategies to maximize material efficiency in order to make RLVs possible so that access to space becomes affordable and reliable is provided. Also, the economic viability of the RLVs is examined to show the extent to which the use of RLVs has on the reduction of space mission costs. The environmental and economic implications of the increase in the number of space missions as a result of the use of RLVs are also discussed. These research questions are studied through detailed critical analysis of the literature, such as published reports, books, scientific articles, and journals. A combination of keywords such as material efficiency, circular economy, RLVs, and spacecraft materials were used to search for appropriate literature.

Keywords: access to space, circular economy, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 112

Authors: Hamda M. Al-Ali

Abstract:

The ultimate aim of space exploration has been centralized around the possibility of life on other planets in the solar system. This aim is driven by the detrimental effects that climate change could potentially have on human survival on Earth in the future. This drives humans to search for feasible solutions to increase environmental and economical sustainability on Earth and to evaluate and explore the ability of human survival on other planets such as Mars. To do that, frequent space missions are required to meet the ambitious human goals. This means that reliable and affordable access to space is required, which could be largely achieved through the use of reusable spacecrafts. Therefore, materials and resources must be used wisely to meet the increasing demand. Space missions are currently extremely expensive to operate. However, reusing materials hence spacecrafts, can potentially reduce overall mission costs as well as the negative impact on both space and Earth environments. This is because reusing materials leads to less waste generated per mission, and therefore fewer landfill sites are required. Reusing materials reduces resource consumption, material production, and the need for processing new and replacement spacecraft and launch vehicle parts. Consequently, this will ease and facilitate human access to outer space as it will reduce the demand for scarce resources, which will boost material efficiency in the space industry. Material efficiency expresses the extent to which resources are consumed in the production cycle and how the waste produced by the industrial process is minimized. The strategies proposed in this paper to boost material efficiency in the space sector are the introduction of key performance indicators that are able to measure material efficiency as well as the introduction of clearly defined policies and legislation that can be easily implemented within the general practices in the space industry. Another strategy to improve material efficiency is by amplifying energy and resource efficiency through reusing materials. The circularity of various spacecraft materials such as Kevlar, steel, and aluminum alloys could be maximized through reusing them directly or after galvanizing them with another layer of material to act as a protective coat. This research paper has an aim to investigate and discuss how to improve material efficiency in space missions considering circular economy concepts so that space and Earth become more economically and environmentally sustainable. The circular economy is a transition from a make-use-waste linear model to a closed-loop socio-economic model, which is regenerative and restorative in nature. The implementation of a circular economy will reduce waste and pollution through maximizing material efficiency, ensuring that businesses can thrive and sustain. Further research into the extent to which reusable launch vehicles reduce space mission costs have been discussed, along with the environmental and economic implications it could have on the space sector and the environment. This has been examined through research and in-depth literature review of published reports, books, scientific articles, and journals. Keywords such as material efficiency, circular economy, reusable launch vehicles and spacecraft materials were used to search for relevant literature.

Keywords: circular economy, key performance indicator, material efficiency, reusable launch vehicles, spacecraft materials

Procedia PDF Downloads 124

Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

Abstract:

Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

Procedia PDF Downloads 131

Authors: Ammar Alali, Mahmoud Abughaban

Abstract:

Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

Procedia PDF Downloads 226

Authors: Hamda Ajmal, Karen Young, Ruth Melia, John Bogue, Mary O'Sullivan, Jim Duggan, Hannah Wood

Abstract:

The Covid-19 pandemic led to a range of public health mitigation strategies in order to suppress the SARS-CoV-2 virus. The drastic changes in everyday life due to lockdowns had the potential for a significant negative impact on public mental health, and a key public health goal is to now assess the evidence from available Irish datasets to provide useful insights on this issue. Text-50808 is an online text-based mental health support service, established in Ireland in 2020, and can provide a measure of revealed distress and mental health concerns across the population. The aim of this study is to explore statistical associations between public mental health in Ireland and the Covid-19 pandemic. Uniquely, this study combines two measures of emotional wellbeing in Ireland: (1) weekly text volume at Text-50808, and (2) emotional wellbeing indicators reported by respondents of the Amárach public opinion survey, carried out on behalf of the Department of Health, Ireland. For this analysis, a multivariate graphical exploratory data analysis (EDA) was performed on the Text-50808 dataset dated from 15th June 2020 to 30th June 2021. This was followed by time-series analysis of key mental health indicators including: (1) the percentage of daily/weekly texts at Text-50808 that mention Covid-19 related issues; (2) the weekly percentage of people experiencing anxiety, boredom, enjoyment, happiness, worry, fear and stress in Amárach survey; and Covid-19 related factors: (3) daily new Covid-19 case numbers; (4) daily stringency index capturing the effect of government non-pharmaceutical interventions (NPIs) in Ireland. The cross-correlation function was applied to measure the relationship between the different time series. EDA of the Text-50808 dataset reveals significant peaks in the volume of texts on days prior to level 3 lockdown and level 5 lockdown in October 2020, and full level 5 lockdown in December 2020. A significantly high positive correlation was observed between the percentage of texts at Text-50808 that reported Covid-19 related issues and the percentage of respondents experiencing anxiety, worry and boredom (at a lag of 1 week) in Amárach survey data. There is a significant negative correlation between percentage of texts with Covid-19 related issues and percentage of respondents experiencing happiness in Amárach survey. Daily percentage of texts at Text-50808 that reported Covid-19 related issues to have a weak positive correlation with daily new Covid-19 cases in Ireland at a lag of 10 days and with daily stringency index of NPIs in Ireland at a lag of 2 days. The sudden peaks in text volume at Text-50808 immediately prior to new restrictions in Ireland indicate an association between a rise in mental health concerns following the announcement of new restrictions. There is also a high correlation between emotional wellbeing variables in the Amárach dataset and the number of weekly texts at Text-50808, and this confirms that Text-50808 reflects overall public sentiment. This analysis confirms the benefits of the texting service as a community surveillance tool for mental health in the population. This initial EDA will be extended to use multivariate modeling to predict the effect of additional Covid-19 related factors on public mental health in Ireland.

Keywords: COVID-19 pandemic, data analysis, digital health, mental health, public health, digital health

Procedia PDF Downloads 142