IJCSNS International Journal of Computer Science and Network Security, VOL.21 No.8, August 2021 267 Manuscript received August 5, 2021 Manuscript revised August 20, 2021 https://doi.org/10.22937/IJCSNS.2021.21.8.35 Lifesaver: Android-based Application for Human Emergency Falling State Recognition Qaisar Abbas † † College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia Summary Smart application is developed in this paper by using an android- based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain. Key words: Mobil application, Android application, Healthcare, Detection of fall down state, sensor, disable human, Machine learning, Artificial neural network 1. Introduction Lifesaver is the smart application used to detect and recognize a fall state of humans in case of emergency situations. This application can save humans in case of a dangerous accident and a lot of people get fall when they outside or alone at home, and sometimes they didn’t survive. Following a fall, older individuals who live alone are at a higher risk of receiving delayed help. A low-cost, inconspicuous device capable of automatically detecting falls in the homes of elderly people might dramatically minimize the number of people who require assistance [1] later. This problem is common for the elderly in which there is one from every three persons in the United States exposed to fall (In 2010 there was 2.3-million-person exposure to fall 662,000 needed to anesthesia and cost the US Treasury approximately $ 30 billion) [2]and leads to causing concern for their families. The worst thing here is there are about 10,000 deaths every in the U.S. that occur due to fall accidents [3]. The Lifesaver application idea is too important not just for the elderly even for most disabled such as blind, deaf, and dumb. Because there are a huge number of smartphones users, interested in this topic focus on the development of new fall detection systems especially that smartphones already have communication facilities like SMS and GPS [4]. in this app we take the elderly, deaf, blind, and disables people as intended to help them when they alone and fall. A lot of people especially the elderly vulnerable to fall so we seek this application to save their life in the quickest way. A visual example of different emergency situations is illustrated in Fig.1. The Lifesaver mobile application is developed in this paper to create an application for emergencies smartphones that might be exposed to humans, and the risk is described that the person making the request to call a friend or an ambulance to help the injured and he gets through this smart application to clear and the period will help the application to increase the speed save a person through the application and save time by selecting the location using GPS. For example, if a person falls down and there is a car accident. In this paper, a smart algorithm is developed to detect the emergency state of humans in case of a fall downstate or car accident. To develop the Lifesaver application, the perfect threshold is to determine the status of the fall person with high sensitivity and accuracy and use Oracle database GPS and accelerometer and orientation sensor data to detect fall down. To develop this Lifesaver application, the studio robot scout Tools API is mostly utilized. The rest of the paper is organized as follows. Section 2 presents the background and some related work. The system design and data set collections are presented in Section 3 and system implementation in Section 4. In Section 5, the proposed system is evaluated and compared