{'fraction_non_alphanumeric': 0.021775544388609715, 'fraction_numerical': 0.02543018120907568, 'mean_word_length': 4.7766051011433595, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Remote monitoring of a premature infants incubator

Received Jul 14, 2019 Revised Sep 15, 2019 Accepted Sep 30, 2019 In this paper, the air temperature and humidity levels in the infant' incubator are monitored remotely by means of Arduino microcontroller with different sensors and an open source internet of things (IoT) applications. The system is connected to a network via a wireless fidelity (Wi-Fi) connection to be linked to an application on the smart phone or to the computer. The system is designed using Arduino microcontroller, DHT11/DHT22 sensor for measuring the body parameters, such as the temperature and the humidity, LCD monitor, ESP8266 WiFi modules, and NodeMCU-v3. The results have shown that real time updated medical records can be transferred to the medical staff utilizing ThingSpeak IoT applications.


METHODOLOGY
shows the block diagram of the temperature and humidity detector DHT11 for the incubator. The Arduino UNO as a microcontroller, liquid crystal display (LCD), ESP8266 WiFi module to transmit the temperature and humidity data remotely to the ThingSpeak, which is an open source IoT and application programming interface (API) to store and retrieve data from the sensors.  Figure 2 shows the block diagram of the temperature and humidity detector with the NodeMCU-v3, which is an open source IoT platform based on the ESP8266 Wi-Fi system on a chip. Compared to the Arduino Uno, the NodeMCU-v3 platform has more powerful processor than the Arduino's Atmega328, with 4 Mb flash memory and much more random-access memory (RAM). The advantages of using NodeMCU-v3 over the ESP8266 WiFi module with Arduino UNO is the ease of use and program with no connection problems that have been encountered with the latter module. In Figure 1, pin number 5 of the Arduino UNO receives the signal from DHT11 sensor and processes the received data and sends it to the WiFi ESP8266 module. This module is an independent system-on-chip (SOC) that provides WiFi access to the microcontroller utilizing transmission control protocol (TCP) / internet protocol (IP) scheme. In addition, this module has the ability to host an application and it can also deliver the WiFi networking functions from another application processor. The ESP8266 module has an AT command instructions pre-installed to control the modem. The measured data are sent to the ThingSpeak API and it displayed as a graph. DHT11 sensor measures the humidity and the temperature with a relative range of 20-95 % for the humidity and 0-50 o C for the temperature, respectively. The cost of this sensor is quite inexpensive with respect to its operating range that has accuracy of ±5% for the humidity and ± 2 o C for the temperature. However, the new version DHT22 has more precision over a slightly larger range. Utilizing this method will provide an easy and precise way to monitor the incubator at any time and place with low cost using any available gadget and the account information of the ThingSpeak.

RESULTS AND DISCUSSION
The results of our experiments for the proposed monitoring system will be presented and discussed in this section. The temperature and humidity measured data are updated continuously and monitored utilizing the remote ThingSpeak IoT application.
Screen shot for the detected parameters on the serial monitor as shown in Figure 3. The DHT11 uses the exclusive digital-signal-acquisition technique and temperature and humidity sensing technology, which ensures high reliability and excellent long-term stability. The temperature and humidity of this sensor are recorded at different time instances inside the room for different temperature and humidity values. In Figure 4, the humidity has increased to 75 % when the temperature increased above 33.5 o C, while it is reduced to 37 % when the temperature was below 32 o C as shown in Table 1.  It is observed that, changing the location of the sensor inside the incubator gives different measurements. For instance, when placing the sensor at the left hand side above the incubator heater the temperature was 40 o C, while the temperature has reduced to 34 o C when placed on the center of the incubator as shown in Table 2, which is more realistic to be considered as optimum measuring point inside the incubator. Figure 5 shows the change in temperature and humidity by changing the location of the sensor and humidity with the presence of water in the incubator and in the absence of water. It is observed that the humidity level has increased to 22 % after placing the water inside the incubator after several seconds.  Figure 5. Temperature and humidity monitoring using DHT11 inside an incubator Figure 6 shows the output of DHT22 that has been detected on IoT Thingspeak monitor. By switching the sensors from DHT11 to DHT22 during the interval 14.00 -14.10, it is observed that both temperature and humidity measurements were zero. However, after that time the recorded measurement of the humidity was 50% while the temperature has increased above 25 o C. Real photos of the proposed remote incubator monitoring system as shown in Figure 7.

Error Calculations
Further investigations are performed to verify the results of this paper and to make sure that the transmitted measurements are accurate and reliable. In this section, we compared our measurements to the measurements of the built-in temperature sensor of the incubator. The relative error is measured using [25], relative error = |Experimental -Theoritical | Theoritical .
The output of the DHT11 was 34 o C at the time instance 13.15 sec, while the incubator temperature at that time was 35 o C, the relative error was 0.0285. Similarly, the DHT22 measured temperature was 37 o C at time 14.15 sec, while the incubator temperature at that time was 37.2 o C, the relative error was 0.0053.

Technical Specifications
Technical specifications as shown in Table 3.

CONCLUSION
In conclusion, this paper proposed a remote monitoring system for the infant incubator utilizing Arduino microcontroller, D‫أ‬HT11 and DHT22 sensors with ESP8266 WiFi module and NodeMCU V3. It is observed that utilizing NodeMCU-v3 as a wireless module has facilitated the work and provided more accuracy than using the ESP8266 WiFi module. The proposed system has shown accurate and reliable temperature and humidity level measurements and transmitting via IoT module. The remote monitoring are achieved using smart mobiles or computers which provided low cost method for remote monitoring with very small tolerance compared to the incubator built-in sensors.