Nowadays, it is essential to use all concepts of Human-Computer interaction to understand mobile application design usability. This manuscript aimed to analyze a mobile application user experience (Grab online transportation), especially Grab foodservice users, using a user experience questionnaire since we noticed some Grab food users' complaints.  Researchers collected data from 90 respondents within six were not used because the excel data analysis tool found that there were suspicious. We finally analyzed using an excel data analysis tool. The findings have shown that all six scales of the User Experience Questionnaire (UEQ) are good except the dependability scale. In addition, the mean scale value computed is favorable, and all values are more significant than 0.8 compared to the UEQ benchmark. The findings can be used for dependability improvement to reduce complaints from users.

Covid-19 has become an issue in medical research since its inception with more than 45million positive patients in the World. IoT is beneficial in Health for effective Monitoring of Covid-19 cases through Networks. The purpose of this study is to suggest an IoT design for smart monitoring and emergency alert system for covid-19 patients which will monitor a patient who is in stage 1 of the disease using sensors like Temperature sensor, Blood Oxygen level and Heart rate sensor and Arduino Uno Controller which will gather information from the patient and send to the IoT server. The authors expect that the proposed system will be reliable and effective in reducing mortality and hospital admissions by saving lives in emergencies and alerting. Further, the system is made to generate message warnings to the nearest hospital compare to the location of the patient within he is under extreme conditions. It can be ended up that Smart monitoring and emergency alert System is important for monitoring covid-19 patients and can alert in case of an abnormal situation of the patient.

Malaria is an infectious disease that has a devastating effect on humans but is contagious and preventable. There were 228 million malaria cases globally in 2018, with 93% of patients and 94% dying showing up in Africa within Burundi, possessing a massive growth (51%). This study proposes an IoT design for smart monitoring and alert systems for malaria patients in Burundi. After being tested positive while they are home drinking tablets prescribed by the doctor, the patients will use a body temperature sensor. When the situation worsens, the patient shall be hospitalized and use the water level sensor to monitor the serum level, which contains quinine. Body temperature and water level sensor will be connected to Arduino Microcontroller, and all information will be gathered and sent to the IoT server through the internet. The system design is authentic and adequate in reducing mortality in Burundi. Besides, the system is equipped to set up a caution message to the medical staff in case of the patient's extreme conditions. It can be concluded that a Smart monitoring and alert system is essential for monitoring malaria patients and can alert in case of a severe condition.

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