Innovative IOT Covid-19 Monitoring System to Ameliorate Medical Professionals

Special quarantine centers setup to handle COVID-19 patients have experienced an overflow of patients as cases of the infectious disease keep on rising. Doctors assigned to these quarantine centers have had a difficult time keeping track of the health conditions of the patients in quarantine. The doctors assigned to such setups have an increased risk of infection due to their interactions with the patients. In order to enable the health workers to efficiently monitor the quarantined patients and reduction of in-service infections, this study proposes to design an innovative IOT based using IOT Gecko platform health monitoring system able to remotely monitor the health of the patients and send automated reports to doctors’ over a set internet connection. The proposed system will be equipped with heartbeat sensor, temperature sensor and BP Sensor to keep track of respective health conditions of the patients. If successfully designed and implemented, the systems will be enable doctors to remotely monitor patient’s heartbeat, temperature and blood pressure reducing the risks of infection and increasing the number of patients a single doctor can monitor at a time.

Factors Influencing Temperature Measurements from Miniaturized Thermal Infrared (TIR) Cameras: A Laboratory-Based Approach

The workflow for estimating the temperature in agricultural fields from multiple sensors needs to be optimized upon testing each type of sensor’s actual user performance. In this sense, readily available miniaturized UAV-based thermal infrared (TIR) cameras can be combined with proximal sensors in measuring the surface temperature. Before the two types of cameras can be operationally used in the field, laboratory experiments are needed to fully understand their capabilities and all the influencing factors. We present the measurement results of laboratory experiments of UAV-borne WIRIS 2nd GEN and handheld FLIR E8-XT cameras. For these uncooled sensors, it took 30 to 60 min for the measured signal to stabilize and the sensor temperature drifted continuously. The drifting sensor temperature was strongly correlated to the measured signal. Specifically for WIRIS, the automated non-uniformity correction (NUC) contributed to extra uncertainty in measurements. Another problem was the temperature measurement dependency on various ambient environmental parameters. An increase in the measuring distance resulted in the underestimation of surface temperature, though the degree of change may also come from reflected radiation from neighboring objects, water vapor absorption, and the object size in the field of view (FOV). Wind and radiation tests suggested that these factors can contribute to the uncertainty of several Celsius degrees in measured results. Based on these indoor experiment results, we provide a list of suggestions on the potential practices for deriving accurate temperature data from radiometric miniaturized TIR cameras in actual field practices for (agro-)environmental research.

A Robot for Combat and Calamities with Encrypted WSN

The needs of search and rescue teams in numerous ways reflect the requirements of the military. They both work in perilous situations, they need to discover ways to gather data while keeping personnel out of hurt, and they are both seeking out for individuals. So, this Robot Commands in manual mode using a Smartphone, Wireless cam for Real-time Broadcast, PIR and Metal detection sensors, GPS & GSM modules, ultrasonic sensor, Gas & Fire sensor, temperature and humidity sensor, Acid gun, RFID and Relay switch, In this wireless sensor networks (WSN) is an Encrypted Network and infrastructure-less wireless networks to Screening physical or natural conditions, such as vibrations, pressures,movement, or toxins and to agreeably transmit their information retrieved by using IOT Server.

Smart Ambulance System with Remote Knowledge Communications Through Cloud

An ambulance is one of saving many lives by taking the people who need health emergencies. Saving the life of the person is one of the challenging and precious ones. Our key idea is to deliver a patient’s health condition before the victim reaches the hospital in this project. Here we use some biomedical sensors like a heartbeat sensor, temperature sensor, and a respiratory sensor to check the patient health status. There will be a continuous update to the hospital about the patient’s condition through the cloud with the help of the internet of things. The hospitals can also track the ambulance’s live location through the GPS placed in the ambulance where it arrives, and they can know at what time the patient reaches the hospital. With this information, if the patient is in critical condition, the hospital staff can make all the earlier arrangements before the patient arrives at the hospital and saves their lives as soon as possible. Here we use the biometric sensor to know the patient’s information by scanning the patient’s fingerprint. The stored database obtains this information. In cases of accident situations, to avoid legal problems, the patient’s information is sent to the cops through the GSM, and it is also intimated to the patient’s relatives as soon as possible. The parameters which are measured by using biomedical sensors are viewed by doctors using the Blynk app.

Sistem Pendeteksi Kebakaran Pada Apron Passenger Bus (APB) Berbasis Mikrokontroler

This research is about constructing a prototype of fire detection warning system on Apron Passenger Bus. The prototype can detect certain possibility of fire and give early warning to the driver. It works automatically based on three sensors used, which are smoke sensor, temperature sensor and flame sensor. The prototype is constructed using these three sensors and combined with Arduino microcontroller. This microcontroller has a role of transmitting information to the alarm system as a fire indicator. Method used in this research begins with simulation of a fire warning system and continued by implementation on hardware. The prototype works successfully on detecting fire both on software and hardware basis.

IoT Based Fire Accident Detection System with Deep Learning Intelligence

A fire accident can be caused by many hazards, such as a propane tank, a defective product, a vehicle crash, or poor workplace safety. Because accidents involving fire are often unexpected and sudden, there isn’t a standard legal process for dealing with them, other than filing a negligence or workers compensation claim. This project aims to detect and monitor Fire Accident incidents well in advance and alert the surroundings to minimize the losses. This is an integration of IoT and Deep Learning Technologies, where sensors are used to collect the relevant data under the supervision of a controller unit. The controller unit collects and sends this data to a cloud database, from where the data for the Deep Learning model is fetched. This data is then used for making some insights and further predictive analytics. From the insights, many variables were found to be one of the reasons for a fire accident to take place. We considered the information about variables like Flame sensor, Temperature, Heat Index, GPS coordinates, Smoke, Type of Gases, Date, and Time for feature set generation and fed the model to a deep neural network for making future predictions. Comparing to existing conventional methods, this proposed method is different in terms of integrating deep learning with IoT. This method of approach will predict the chance of accidents priorly by classification of data.

The PRESSURE AND TEMPERATURE MONITORING SYSTEM OF ROCKET MOTORCYCLE COMBUSTION BASED ON RASPBERRY PI 4.0

– Rockets have an important role in today's era because they really help the activities carried out by the Indonesian National Army in order to maintain the integrity of the Unitary Republic of Indonesia. Raspberry pi 4.0 has several advantages and 2 functions, namely as a microprocessor and microcontroller. The monitoring system for the pressure and temperature of the rocket motor combustion chamber is made in such a way by using the red node software so that it can find out real-time data on the pressure and temperature of the resulting rocket motor combustion chamber. The pressure and temperature monitoring system of the rocket motor combustion chamber is equipped with a pressure transducer sensor, temperature sensor and load cell as the rocket load will be maximized by 1 ton. Control data generated from the pressure and temperature of the motor combustion chamber is sent to the raspberry pi via serial communication. This research was conducted based on pure experiments.

Pemantau Gas Metana, Suhu, dan Kelembaban sebagai Penyebab Efek Rumah Kaca Dipadang Lamun Berbasis Internet Of Things

Seagrass is a plant that covers coastal areas/shallow seas that can produce methane gas (CH4) during the decomposition process. The occurrence of decay caused by microbes in seagrass plants that have died in the process produces methane gas (CH4) as the cause of the greenhouse effect. Methane gas monitoring system (CH4) is proposed using MQ-4 sensor, temperature and humidity sensor (DHT11) using NodeMCU ESP8266 module, SD Card module as backup data storage and processed with local database and through mysql database the data will be displayed on the website page for information. . From the tests carried out, the response time for DHT11 is 5.6 seconds and MQ-4 is 1.5 seconds. It has a reading sensitivity rate of 99.92% for DHT11, 99.997% for MQ-4. The accuracy rate for DHT11 is a multiple of 1. For the MQ-4 sensor it has an accuracy level of 2 digits behind the comma. The tool has a data transfer rate of up to that which appears on the front-end 0.2736. With this tool, checking measurement results can be done quickly and can be done from anywhere.

Correction of Biogeochemical-Argo Radiometry for Sensor Temperature-Dependence and Drift: Protocols for a Delayed-Mode Quality Control

Measuring the underwater light field is a key mission of the international Biogeochemical-Argo program. Since 2012, 0–250 dbar profiles of downwelling irradiance at 380, 412 and 490 nm besides photosynthetically available radiation (PAR) have been acquired across the globe every 1 to 10 days. The resulting unprecedented amount of radiometric data has been previously quality-controlled for real-time distribution and ocean optics applications, yet some issues affecting the accuracy of measurements at depth have been identified such as changes in sensor dark responsiveness to ambient temperature, with time and according to the material used to build the instrument components. Here, we propose a quality-control procedure to solve these sensor issues to make Argo radiometry data available for delayed-mode distribution, with associated error estimation. The presented protocol requires the acquisition of ancillary radiometric measurements at the 1000 dbar parking depth and night-time profiles. A test on >10000 profiles from across the world revealed a quality-control success rate >90% for each band. The procedure shows similar performance in re-qualifying low radiometry values across diverse oceanic regions. We finally recommend, for future deployments, acquiring daily 1000 dbar measurements and one night profile per year, preferably during moonless nights and when the temperature range between the surface and 1000 dbar is the largest.

Analisis Kelayakan Air Berbasis Android

This research was conducted to identify the test of the water quality which good for consumption. It can be proved from temperature, turbidity level, and TDS (Total Dissolved Solids). By tempting the sensor, the turbidity and TDS meter controlled with the Arduino uno and the MCU node is forwarded to send data to the bylink application. The bylink application will help in monitoring water conditions by displaying the water condition which fit for consuming. The method used in this research was started with making a prototype then producing data to determine the feasibility of water through the TDS sensor, temperature sensor, and NTU (water clarity). This indicators were developed on an Android system whom the user could determine feasibility water easier.