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In developing countries, traditional access management systems ubiquitously use either keypad based password protection or radio frequency identification (RFID) card based protection. With the increased number of threats in recent years, these systems are becoming more vulnerable. If the password or the RFID card is somehow compromised, any unautho...
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... matched with the stored data, then the access is granted and an AES encrypted grant response is sent to the Node JS based cloud server. Upon receiving this message and decrypting it, the web server will send a verification SMS to the user and a notification SMS to the system administrator. The flow chart of the system is given in the following figure(Fig. 2). ...
Citations
... Upon acquitting all the sensor data at a specific time, they are sent to the coordinator radio. Inspired by the nested conditional algorithm [19], [20] and [21], the router side software design is developed and shown in the flow chart in figure 4. ...
Indoor environment condition monitoring is more
focused in recent years, and ubiquitous computing is surrounding
us with a convenient and comfortable information environment
that is combining physical and computational infrastructures
into an integrated environment. This environment is featuring
an explosion of hundreds or thousands of computing devices and
sensors that provide new functionality, offer specialized services,
and boost productivity. However, for different situations and
different infrastructure, the environment condition monitoring
parameter varies remarkably. In the case of previously developed
systems, three to four environmental parameters were analyzed,
and data was not available on a remote device. The observation
of sequential change in monitoring parameters is also crucial for
many applications. In this paper, five independent parameters,
i.e., temperature, barometric pressure, humidity, luminance, and
gas concentration, are measured independently in each WSN
node. The data is encrypted via the AES algorithm on the router
side and decrypted on the coordinator side. After the data is
received by the coordinator node of WSN and send to the IoT
server where the real-time data is plotted with respect to time,
the data can be monitored for analysis from the remote android
device since a dedicated android application is developed for
this. The WSN data transfer efficiency is measured with respect
to Received Signal Strength Intensity (RSSI). Even though the
power consumption of Zigbee is about 2mW, at 600m distance,
the value of RSSI is found -69.17dBm.
Today's and tomorrow's secret data exchange relies heavily on cryptography. Cryptographic applications offer a secure communication channel for safely transferring data. It provides individuals, groups, and organizations with greater privacy and access to communication and other information, as well as the opportunity to restore personal privacy. Nowadays, online users desire to create an account in order to get access to certain websites, such as online tutorials, online purchases, online resource access, hosting services, social networking sites, and so on. However, unless the service provider or authority person ensures that the registration and login processes are genuine, there is a potential that the account might be hacked by a third party using the ordinary user access method. With the growing usage of cloud emails and frequent reports of large-scale leakage occurrences, a security attribute known as forward secrecy becomes desired and necessary for both users and cloud service providers to improve the security of cloud email systems.
The development of a cleanroom monitoring system needs more concentrated consideration consistently. There is a challenge to prove that the cleanroom operates following the specifications, in other words, users do not see the software error, they see failures in execution. This paper aims to design a smart monitoring system to monitor important parameters inside the cleanroom, i.e. temperature, humidity, and pressure to produce a good quality of work or experiment inside the cleanroom. The observing framework utilizes Arduino Mega as a microcontroller, ESP 8266 Wi-Fi module, DHT 11 as an integrated temperature and humidity sensor, HX710B as a pressure sensor, and Blynk application as a monitoring system to record and show information including provide fault notification. The project is tested on a modeled cleanroom to monitor important parameters via smartphone anytime and anywhere. From the experimental results, the Cleanroom IoT Monitoring System successfully read all parameters based on the system requirements and displays data of parameters in real-time and stored historical data. This system is also successful to provide failures notification of humidity, temperature, and pressure in real-time if any of the parameters are out of range from the system requirements. Lastly, users can monitor the condition of the cleanroom anytime and anywhere including receiving real-time failures notifications. This concept can avoid or reduce cleanroom working out of the criteria that can cause testing or experiment inside the cleanroom to be inaccurate. By observing and controlling the prerequisite development for IoT monitoring systems, great nature and better quality of performance of operational cleanrooms can be delivered.
