29 Page 29-32 © MAT Journals 2020. All Rights Reserved Volume-5, Issue-1 (January-April, 2020) http://doi.org/10.5281/zenodo.3755238 Journal of Electronics and Communication Systems www.matjournals.com IOT Based Patient Fall Prediction And Detection System Amol Patil *1 , Mayuri Gaikwad 2 , Harshali Gaikwad 2 , Swati Gavhar 2 , Harshal Galwade 2 1 Assistant Professor, 2 Undergraduate Student Department of Electronics and Telecommunication Engineering, Jawahar Education Society's, Annasaheb Chudaman Patil College of Engineering, Kharghar, Navi Mumbai, India *Corresponding Author: agpatil@acpce.ac.in ABSTRACT This Paper states that fall detection and fall prevention systems should require people to wear or to interact with devices. To monitor the system in 24/7 surveillance camera-based systems do not have a monitoring system as no object is attached here the sensors have to be active obstructiveness is varies from system to system as per the sensor used. Some systems need additional gadgets like a wrist band or a belt this has a data collection and robust with a more responsive system. It does not depend on wireless communication. Usually, it means bigger and more obstructive devices. We are tending to develop such a device that can alert and predict patient falls to prevent any injury due to falling. Keywords-- Falling Detection, IoT based Monitoring, Sensor INTRODUCTION The worldwide population of elderly who are more than 65 years old is expected to grow to 1 billion in 2030, and the percentage of individuals aged 20–64 years will become 35% of the population. There are many vital signals like application patients and people wear sensors to detect the emergency condition. A fall is one of the key factors that can lead to injuries and decrease quality of life, at times resulting in the death of elderly persons. People’s rate of falling increases with their age [1]. Falls occur frequently in medical health care centers, hospitals, or houses, with approximately 30% of falls causing injury. Falls in hospitals occur in the rooms of the patients (84%) and during the transfer from one place to another (19%). Majority of falls is due to chairs and beds who falls in a nursing home or hospitals the reason for fall can be aggravated by chronic disease such as Osteoporosis, Delirium, and the aging person is identified by the location of fall, time of fall duration in such an incident it is important to have rescue staff so that the family can be informed about the incident through mobile or wireless network. Microelectron mechanical has different sensors and wireless networks. Wireless sensor networks (WSNs) comprise several tiny and small sensor nodes which are deployed over several applications to monitor the physical environment (e.g., temperature, humidity, vibration, pressure, etc.) physiological parameters are used to monitor the Heart rate, Blood pressure, Fall detection, etc. are the patient vital signs. WSN has played a significant role in medical applications for monitoring elderly patients’ vital signs [2]. The power consumption problem of the proposed fall detection system (FDS) is also addressed. Fall detection is of three types in that the first one is a vision based that is the computer to capture images or videos and is subdivides are GB camera, 3D based method employing several cameras. This system monitors the shape and position of the subjects, which depends on image processing pre- processing and pattern recognition techniques. These are convenient and obstructive for elders and more expensive than the other two types because it needs a camera. Besides, the RGB camera needs to be calibrated to allow a 3D reconstruction of the body, resulting in a time-consuming and computationally intensive procedure. ORGANIZATION OF REPORT The report is divided into four chapters. Each chapter is giving brief information about the project. The first chapter is the introduction of the report, it discusses how the ancient patient caretaking changes to high-tech patient fall prediction and detection system and how convenient it is. The second chapter is a literature survey; it discusses the improvement in the system used for patient monitoring. The third chapter gives an overall system overview. It will provide information about the block diagram, circuit diagram, and all components and its proper working [3]. Chapter four is the project’s advantages, future enhancement and conclusion of it as shown in Fig. 1.