Facility maintenance management system based on GIS and indoor map

This research presented a system development approach for facility maintenance management system based on GIS and indoor map in the form of web applications that can be used with all devices and no worries about time limitations. The capabilities of GIS, indoor map, and geospatial data visualization help speeding up facility maintenance management process and create benefits to all concerned parties, i.e., users can notify and follow the data of facility errors at the time; or officers in charge can operate quickly because they can access real-time data. Indoor map display makes it easier to access locations or places of damaged facilities. In addition, the data from the model system presented in this research can also be applied to planning and decision-making of executives

Machine Learning Based Emergency Patient Classification System

Public Health Office and the risk map created from the patient information. Many provincial hospitals currently have to admit a large number of patients to their emergency room. Each year, the number outgrow limited medical resources, causing tremendous operational delay, and thus undermining quality of medical services. In addition, existing ER flows remain lacking means of communicating with patients’ relatives and notifying them with treatment status of patients under their care. To addresses these concerns, registered nurses with experiences are required not only to make initial patient screening and prioritization, but also to serve as liaison between physicians and patients’ relatives. These double tasks impose great burden to already overloaded medical staffs. An emergency patient classification system, based on support vector machine was developed. It was implemented as a web application, written in PHP, and running on MySQL database. GIS technology was employed to analyze spatial data and producing relevant reports. The proposed system could classify emergency patient into different groups based on their severity, according to the government standard. The resultant recommendation, verified by a nurse on duty, as well as treatment status were presented to patients’ relatives on a digital screen. Moreover, the hospital was able to use the summarized reports, in both standard and spatial forms, for its managerial purposes. The develop system could help the hospital to make the most of their limit resources for treating emergency patients. The produced reports were useful for making relevant policies and executive planning

Machine Learning Based Emergency Patient Classification System

Public Health Office and the risk map created from the patient information. Many provincial hospitals currently have to admit a large number of patients to their emergency room. Each year, the number outgrow limited medical resources, causing tremendous operational delay, and thus undermining quality of medical services. In addition, existing ER flows remain lacking means of communicating with patients’ relatives and notifying them with treatment status of patients under their care. To addresses these concerns, registered nurses with experiences are required not only to make initial patient screening and prioritization, but also to serve as liaison between physicians and patients’ relatives. These double tasks impose great burden to already overloaded medical staffs. An emergency patient classification system, based on support vector machine was developed. It was implemented as a web application, written in PHP, and running on MySQL database. GIS technology was employed to analyze spatial data and producing relevant reports. The proposed system could classify emergency patient into different groups based on their severity, according to the government standard. The resultant recommendation, verified by a nurse on duty, as well as treatment status were presented to patients’ relatives on a digital screen. Moreover, the hospital was able to use the summarized reports, in both standard and spatial forms, for its managerial purposes. The develop system could help the hospital to make the most of their limit resources for treating emergency patients. The produced reports were useful for making relevant policies and executive planning.</p

Intelligent Dust Monitoring Application in Patient Room

Due to an ongoing epidemic, the number of hospitalized bedridden patients has increased. It is imperative to closely monitor the hospital room and maintain and clean it regularly to avoid harm to the patients. The accommodations may not be within the standards for a bed-bound patient’s room. The patient has a risk of contracting a respiratory disease, or having an asthmatic attack, if exposed to high levels of PM1, PM2.5, or PM10 dust that cannot be seen with bare eyes so the risk factor is not easy to notice. The goal of this study was to develop a dust monitoring system for hospital bedrooms using IoT, so that the caregivers can monitor air quality in the room. By applying the Internet of Things (IoTs) technology to communicate between sensors and mobile phones, the internet serves as the medium for communication. The demonstration system in the room was equipped with 5 sensor cluster, each measuring: temperature, humidity and dust sensors for PM1, PM2.5, and PM10. Decision trees were trained to predict the outcome of cases after collecting data. The final decision tree model reached an overall classification accuracy of 92.8%. The system could alert for housekeeping or turn on or off an automatic dust remover based on the amount of dust in the room. It also supports cleaning and dust removal to ensure that the bed patient’s room is appropriate and reduces the risk of respiratory diseases caused by dust

Gamification Smartphone Application for Leg Physical Therapy

The need to treat illnesses or deterioration of the legs caused by accidents, rheumatism, muscular weakness, paralysis or bone diseases has increased. Paraplegic patients need physical therapy to mitigate their condition. This study developed a gamification smartphone application for leg physical therapy. The application was implemented for patients using Android Operating System smartphones. The smartphone was attached to the walking support equipment. The accelerometer sensor of the smartphone was utilized to measure distance, time, and number of steps. The application acquired data from the sensor, and processed and stored the data in a server, to enable assessment of critical conditions. Moreover, this system would report the evaluation of physical therapy on a weekly basis. Alerts of physiotherapy treatment could be set in this application. The advantages of the application include increasing the patient’s motivation for the therapy, performed by themselves at home, and the results could be used for planning treatments by a physician

Gamification Smartphone Application for Leg Physical Therapy

The need to treat illnesses or deterioration of the legs caused by accidents, rheumatism, muscular weakness, paralysis or bone diseases has increased. Paraplegic patients need physical therapy to mitigate their condition. This study developed a gamification smartphone application for leg physical therapy. The application was implemented for patients using Android Operating System smartphones. The smartphone was attached to the walking support equipment. The accelerometer sensor of the smartphone was utilized to measure distance, time, and number of steps. The application acquired data from the sensor, and processed and stored the data in a server, to enable assessment of critical conditions. Moreover, this system would report the evaluation of physical therapy on a weekly basis. Alerts of physiotherapy treatment could be set in this application. The advantages of the application include increasing the patient’s motivation for the therapy, performed by themselves at home, and the results could be used for planning treatments by a physician

Land Use and Land Cover Change Detection for Water Yield Estimation using Remote Sensing Data in Batu Pahat, Johor

Globally, the accelerating urbanization led by industrialization and population growth causes severe environmental degradation. The urban expansion particularly to the conversion of land activities affects the ecosystem services critically. This study helps to fill in the gap of determining water yield in the urban area to reduce water stress due to the spatial land use change. The research objectives are to quantify the spatial land use change in Batu Pahat, Johor in the year 1999, 2010, and 2018. Second, to identify the water yield of Batu Pahat in the years 1999, 2010, and 2018. Third, to determine the relationship between water yield, vegetation, and urban expansion. The methods used are landscape change, water yield simulation, and statistical analysis by using the software included ENVI, ArcGIS, FRAGSTAT, Annual Water Yield InVEST Model, and Microsoft Excel. Raw satellite images were extracted for the year 1999, 2010, and 2018. The supervised classification of LULC (Land Use and Land Cover) was done based on the region created which are built-up area, cleared land, vegetation, and water bodies. This study generates results for the changes in percentage area for each LULC class. The highest percentage of area in Batu Pahat is vegetation while the cleared land ranked lowest. In conclusion, this study will aid in understanding and provided empirical data result for the urban expansion and water yield in Batu Pahat, Johor by using GIS and remote sensing applications to produce land use and water yield map as final output

The Digital Game for Curriculum Public Relations (PR) and Learning Using Unity3D

In the age of digital disruption, universities and educational institutions all over the world provide many bachelor’s, postgraduate, and non-degree curriculums. Information is mostly presented in different forms, i.e., PR on websites, mobile applications, or social media; including field PR at different sites, e.g., department stores and schools. However, the limitations and the problems are that presented information fails to attract or motivate perception, interest, and participation of the target groups. Also, traditional PR requires resources in terms of persons, time, and a large amount of expenditures. Thus, this research aimed to present the development of a game to present information for PR of bachelor’s curriculums using Unity3D, which could reduce the limitation of presentation or PR in the traditional forms. It could also save PR budget and could be done anywhere and anytime

Flood Damage Assessment Geospatial Application Using Geoinformatics and Deep Learning Classification

The data of impacts and damage caused by floods is necessary for manipulation to assist and relieve those impacts in each area. The main issue for data acquisition was acquisition methods that affect the durations, accuracy, and completeness of data obtained. Most data are currently obtained by field survey for data on impacts in each area. However, this method contains limitations, i.e., taking a long time, high cost, and no real-time data visualization. Thus, this research presented the study to develop an application for inspecting areas under impact and damage caused by floods using deep learning classification for flood classification and land use type classification in the affected areas using digital images, remote sensing data, and crowdsource data notified by users through the accuracy assessment application of classification. It was found that deep learning classification for flood classification had 97.50% accuracy, with Kappa = 0.95. Land use type classification had 93.71% accuracy, with Kappa = 0.91. Flood damage assessment process in this research was different from other previous research that used geospatial data for flood damage inspection, e.g., satellite images. In contrast, this research brought damage data notified by users for processing with flood data in each area by satellite image processing and land use types of classification. The proposed application can calculate damage in each area and visualize real-time results in maps and graphs on the dashboard via the application. Besides, the presented method can be used to verify and visualize data of areas under impact and damage caused by floods in different areas