Smart Fire Detector utilizing IoT-based Zigbee Sensor

<pre>There are several differences between the two types of alarm systems, conventional systems and addressable systems. It is important to carefully determine the introduction of a fire alarm system according to the installation environment. Talking about the main difference relates to how the connected device communicates with the main control panel by sending a signal. Cost is another factor that can be a determinant of your chosen fire alarm system. In this paper, we proposed smart addressable fire detection system. In the proposed system, <span>IoT</span> was used and the network was constructed using <span>ZigBee</span> module. In the configured network, it consists of a local server and a control server. The local server controls the addressing sensor and sends the information obtained from the sensor to the control server. The control server receives data transmitted from the local server and enables quick fire action. In the actual implementation, the local server used the Lycra controller and <span>ZigBee</span> module. In addition, the control server used the Raspberry Pi and <span>ZigBee</span> modules and connected to the Ethernet so that the administrator could monitor or control the local server.</pre>

Implementation of a Remote Activation Alarm System by the Citizens of the District of Carabayllo, Lima-Peru

Citizen insecurity is a reality with which we must coexist, the cities of Latin America are among the most violent and insecure in the world. According to the statistics of the National Police of Peru, they report that by 2017 the crimes of theft or robbery were the most common because they had a monthly average of 15348 complaints, equivalent to 66.9% of the total crimes nationwide. The INEI (National Institute of Statistics and Informatics) revealed that in the same year the district of Carabayllo obtained 1.85% of the total complaints in Metropolitan Lima, occupying the 17th place in the ranking of districts with the highest number of complaints for this crime. That is why in the present research work a way to counteract these criminal acts was proposed, the first thing is to be located within the operating range of the RF module, so that the remote transmission control can activate it, the RF module will be connected to the power outlet and the siren. The siren will oversee persuading the criminal, in addition to alerting the neighbors about the events that are happening. It was obtained as a result that the system fulfills its purpose, it can be alerted in real time about some attempted theft or at the instant of a threat situation, only by pressing the button of the remote control we can persuade the criminals either by scaring them with the sound or with the help of the neighbors. Keywords-- Citizen insecurity, RF Module, Siren, Remote Control

Alarm System and Emergency Message from Wheelchair User Emergency Condition

When someone uses a wheelchair, there is still the possibility of an accident to the user, such as when the user suddenly falls down from the wheelchair or the user falls down along with the wheelchair. For notification of emergency conditions for wheelchair users, an alarm system is designed that can send messages to the intended mobile number. The system is designed using Wemos D1 mini, Ultrasonic, MPU-6050 and Proximity E18-D80NK sensors. The conclusion from the measurement and test results are: the value read by the MPU-6050 sensor is taken one axis for each direction when the wheelchair was falling down, Y≤180o for left falling down, X≤50o for right falling down, Z≤65o for forward falling and Z≥140o for backwards falling down. The Ultrasonic sensor works well for detecting the presence of user’s legs and the E18-D80NK proximity sensor works well for detecting the position of the user who is sitting in a wheelchair. Receiving notifications through the BLYNK server works well, not affected by distance provided there is an internet connection connected to the device.

Smart Alarm System (Drowsiness Detection System Review Paper)

With the increase in automative population, accident rates are rising rapidly, one of the major reasons is the state of drowsiness or fatigue. Such fatal incidents can be prevented if the driver is warned in time. With time, several drowsiness alarm systems are been implemented, the system monitors driver’s movements through various techniques, one of the most considerable one is face detection, Open Computer Vision is widely used to detect driver’s movements for a long period of time. A comparative study on different types of approach is summarized in this paper. The main agenda is to help the society to understand more about the techniques and find the most convenient method for them. Keywords: Drowsiness, Face Detection, Mouth Yawn Detection, Open Computer Vision

Validation of Agitated Patient Remote Monitoring Alarm System in the Intensive Care Unit

The purpose of this research is to innovate and develop a vision-based remote monitoring alarm system for agitated patients to provide intensive care unit (ICU) nurses with action warnings for agitated patients during their busy work. After the system is completed, preliminary laboratory verification is carried out, and the results are 94.87% in sensitivity, 97.44% in specificity, and 96.15% in accuracy, which enhances the confidence of the follow-up system in clinical testing.

Real-Time Littering Activity Monitoring Based on Image Classification Method

This paper describes the implementation of real time human activity recognition systems in public areas. The objective of the study is to develop an alarm system to identify people who do not care for their surrounding environment. In this research, the actions recognized are limited to littering activity using two methods, i.e., CNN and CNN-LSTM. The proposed system captures, classifies, and recognizes the activity by using two main components, a namely camera and mini-PC. The proposed system was implemented in two locations, i.e., Sekanak River and the mini garden near the Sekanak market. It was able to recognize the littering activity successfully. Based on the proposed model, the validation results from the prediction of the testing data in simulation show a loss value of 70% and an accuracy value of 56% for CNN of model 8 that used 500 epochs and a loss value of 10.61%, and an accuracy value of 97% for CNN-LSTM that used 100 epochs. For real experiment of CNN model 8, it is obtained 66.7% and 75% success for detecting littering activity at mini garden and Sekanak River respectively, while using CNN-LSTM in real experiment sequentially gives 94.4% and 100% success for mini garden and Sekanak river.

GRAPHICAL METHOD FOR DETERMINATION OF MQ-SERIES GAS SENSOR CIRCUIT PARAMETERS FOR A STAND-ALONE GAS ALARM SYSTEM

Background: MQ-series gas sensors belong to the metal oxide semiconductor (MOS) family of sensors that can sense the presence of many gases. These sensors find their application in gas alarm systems as key components. While necessary sensor circuit output voltage value for alarm point in a stand-alone gas alarm system is desirable, but what exact combination of the sensor circuit parameters is required? Hitherto, the determination of these circuit parameters has not been given much attention in the research community. Aim: the purpose of this work is to explore a structured graphical approach of determination of MQ series gas sensor circuit parameters for a stand-alone gas alarm system that yields desired sensor circuit output voltage value for the alarm point; the main objective of the study was to develop mathematical model equations that relate the: (i) sensor resistance (RS) with the gas concentration (x) and the sensor resistance at standard calibration concentration of the sensor base gas in the clean air (Ro) and (ii) sensor circuit output voltage (VRL), load resistance (RL) and sensor resistance (RS). It is expected from the model equations developed that graphical correlations of the sensor circuits parameters will be generated. Using these graphs for a particular case of an MQ-4 gas sensor under the influence of LPG, the parameters that yield desired sensor circuit output voltage of 2V for 1000 ppm of LPG alarm point will be determined. Methods: Model equations were developed for the sensor dynamics, and based on these model equations, graphs for the determination of required sensor parameters were plotted for a case of MQ-4 gas sensor response to LPG. Results and Discussion: The results yielded optimal values for R_O,R_S and R_L of 20 kΩ, 30 kΩ and 20 kΩ respectively, for alarm settings of 1000 ppm and a desired sensor circuit output voltage of 2 V. Based on determined parameters, the calibration equation for determination of best concentration value for a given value of emulated LPG concentration was developed. Using the method proposed in this study makes the process of determining the MQ-series gas sensor circuit parameters less cumbersome as their value can easily be obtained from the resulting graphs. Conclusions: a structured graphical approach for determination of MQ-series gas sensor circuit parameters for alarm points in a stand-alone gas alarm system showed that using MQ-4 gas sensor and LPG as the target gas, and for a sensor circuit output voltage of 2 V for alarm point at 1000 ppm of LPG, the corresponding value of R_O, R_S and R_L obtained were 20 kΩ, 30 kΩ, and 20 kΩ respectively. Hence, a structured graphical approach is suitable for determining MQ series gas sensor circuit parameters for a stand-alone gas alarm system under the influence of its associated gases.

Smart Crude Desalter Monitoring System Using Capacitance Based Technology

Saudi Aramco operates several electrostatic coalescers for bulk emulsion separation and crude desalting. One of the major challenges in operating electrostatic coalescers is the potential buildup of tight emulsions and a rag layer at the interface layer, which causes short-circuiting of the electrostatic grids which increases the risk excessive carryover of water with the crude. Conventional liquid level instrumentation cannot measure the thickness of emulsion layers since the level taps are at the clean oil and water layers. Consequently, the buildup of emulsions is normally not detected by operators. A capacitance-based emulsion detection system was installed at one of the electrostatic coalescers of a Saudi Aramco facility. The system is comprised of multiple probes installed at various elevations in the vessel. Each probe measures the capacitance of the liquid in which it is immersed in. The data is then transmitted to the DCS, where an algorithm computes the oil/water content. Saudi Aramco developed an enhanced predictive alarm logic and advisory tool using the measured capacitance data so that operations may take preemptive measures to prevent upsets from occurring. The alarm system was tested over an extended period of time and it has shown that it can accurately detect the buildup of emulsions prior to an upset in the electrostatic coalescer. What is unique about the system is that it utilizes a combination of absolute capacitance measurements and capacitance variations in the algorithm. Emulsion buildups are detected by the alarm system hours before a potential upset, providing operators ample time to take preemptive measures such as increasing the demulsifier injection rate, desludging the vessel or lowering the interface level. The system significantly reduced the number of electrostatic coalescer upsets at the facility and crude quality was enhanced. Upon inspection of the probes during shutdowns, no buildup of deposits, which impacts capacitance readings, were found on the probes since a flushing system was installed. The alarm system has been utilized for four years with no major issues. Utilizing the capacitance probes to develop an algorithm for an alarm system is a novel technique to detect emulsion layer buildup hours prior to a potential electrostatic grid upset. Large-scale deployment is more economical as it is more cost-effective than radioactive profilers and is logistically easier to manage.