The majority of the existing gases constitute a risk to the health of humans and the environment in general. There is a wide range of diseases that can arise as a result of exposure to toxic and dangerous gases, which can be a cause of death or serious health problems. More so, deadly explosions may occur as a result of leakages of such gases. However, such consequences can be avoided when these dangerous gases are not detected early. Many researchers have proposed different kinds of systems for the detection of gas leakage, but most of the proposed systems were mainly designed to detect LPG gas. Therefore, in this study, a system is proposed for detecting different kinds of flammable and toxic gases. The gases that are detectable by the proposed system include smoke, Ethanol, CNG Gas, Methane, toluene, propane, Carbon Monoxide, acetone, Hydrogen Gas, and Formaldehyde. The system can detect gases efficiently and release evacuation alarms simultaneously, then send SMS for emergencies. The proposed system is ready to use and can be installed at any work location.

/pdf/a-comprehensive-system-for-detection-of-flammable-and-toxic-3j535aq573.pdf

A comprehensive system for detection of flammable and toxic gases using IoT

Liquefied Petroleum Gas (LPG) is a main source of fuel especially in urban areas because it is clean compared to firewood and charcoal. There is always a danger of the gas leakage as a result of negligence or failure on the regulating valve on the gas cylinder which pose a great danger due to highly flammable nature of the gas. Cases of gas related fire has been on the rise and this can be avoided using a gas leakage detection system and thus the need for development of a microcontroller based cooking gas detector. The use of microcontroller enables development of a high accurate and fast response detection system. The detector incorporate MQ-6 sensor (with gas detection range of 300-10000ppm) as the LPG gas sensor, PIC16F690 microcontroller as the control unit, LCD for displaying gas concentration, a buzzer as an alarm and a number of LEDs to indicate the gas leakage status. The microcontroller senses the presence of a gas when the voltages signal from the MQ-6 sensor goes beyond a certain level and gives an audiovisual alarm. The microcontroller is programmed using PIC assembly language and all the peripherals connected to it through it pins. When the system is powered on the microcontroller lit a green LED to show the absence of a gas leakage. LPG gas is released and the sensor voltage signal monitored using a digital multimeter. Below 2.0V, the green LED is kept lit and when the voltage is more or equal to 2.0V, the microcontroller blinks a red LED and set off an alarm to show the presence of a gas. The detector has a button with which the alarm can be acknowledged. The sensor as a high resistance in clean air. In the presence of LPG gas, the sensor conductivity increases and the characteristic of the sensor is that at 2.0V output from the sensor, the gas concentration is 300ppm, thus the trigger level is 2.0V. Therefore, the microcontroller based gas leakage detector based on PIC16F690 microcontroller and MQ-6 sensor is able to detect gas leakage concentration from 300ppm and give an audiovisual signal.

/pdf/sensor-based-gas-leakage-detector-system-2mtt0j9d74.pdf

Sensor-Based Gas Leakage Detector System

This paper is based on a system which is used to detect various hazardous gases with the help of arduino. This work changes the presently available systems that are set industrial areas and this system can also be used in houses and at work place. The primary aim of the work is to design arduino based hazardous gas detecting system using gas sensors. The toxic gases like butane (also known as LPG), methane and carbon monoxide are sensed and displayed on the LCD display. The concentration of the gasses will be shown in the form of percentage by LCD display.

http://www.ijste.org/articles/IJSTEV2I10132.pdf

Hazardous Gas Detection using Arduino

In past decades, we have witnessed lots of gas leakage diasters all over the world, causing serious casualties, property damage and severe negative social impact. During evacuation after gas leakage incident, the poisonous gas shall be accurately detected. Accordingly, the evacuation routine shall be carefully planned and warned to the evacuating people. Unmanned aerial vehicle (UAV) has been widely regarded as a promising tool to support crowd evacuation. In this paper, aiming at providing an efficient UAV control system for crowd evacuation, we propose a crowd simulation based UAV control system to direct crowd evacuation from the polluted area. The architecture mainly consists of a UAV fleet management module, UAV trajectory planning module, and a crowd simulation module. The architecture forms a closed control loop, emphasizing the inter-operation between the real scenario and the simulation scenario. A case study on UAV gas leakage detection scheduling is given. The results show that the proposed architecture can provide efficient way to help pedestrian in the environment to evacuate and avoid to be infected by the toxic gas.

A Crowd Simulation Based UAV Control Architecture for Industrial Disaster Evacuation

This paper presents the growth in the industrial monitoring system’s design using Internet of Things (IoT). The sensor used for the development of this system is MQ-2 which detects the leakage of gas at any atmos pheric condition and fire sensor as a simple and compact device for protection against fire. In gas sensor system, Ras pberry pi plays an important role such that all the components are interfaced to it. This avails the observer to notice the changes from anywhere in the world. The requirement of a gas detection system is to monitor the surroundings continuously. When gas and smoke is detected then system will send short message service (SMS) to the user then user will take respective action.

Gas Leakage and Fire Detection using Raspberry Pi

Gas leakage is a major problem with industrial sector, residential premises and gas powered vehicles like CNG (compressed natural gas) buses, cars. One of the preventive methods to stop accident associated with the gas leakage is to install gas leakage detection kit at vulnerable places. The aim of this paper is to present such a design that can automatically detect and stop gas leakage in vulnerable premises. In particular gas sensor has been used which has high sensitivity for propane (C3H8) and butane (C4H10). Gas leakage system consists of GSM (Global System for mobile communications) module, which warns by sending SMS. However, the former gas leakage system cannot react in time. This paper provides the design approach on both software and hardware.

/pdf/gsm-based-gas-leakage-detection-system-3vmfa3dc57.pdf

Gsm based gas leakage detection system

A field trial was conducted during kharif 2019 cropping seasons. An attempt was made to find out the effective management practice through application of agrochemicals to minimize vector activites &the crop loss. Three bio rational molecules viz., Imidacloprid 17.8 SL @ 1.0 ml/3liter water, Acetamiprid 20% SP @1.0 gm/ liter water and KEM (Immunity Builder) @2.0 ml/ liter were sprayedat 15 day interval and were evaluated against vector activity to reduce the leaf curl disease incidence. The minimum disease incidence was recorded to the extent of (27.25%) coupled with highest fruit yield of 63.13 q/ha in the treatment T2 having two spraying of Acetamiprid 20% SP @1.0 gm/ liter water at an interval of fifteen days during Kharif 2019 cropping season. Maximum disease incidence (32.25%) in control with lowest yield (54.23/ha). Infection by chili leaf curl disease complex adversely affected yield attributing characters during Kharif season. Highest cost-benefit ratio of 1:11.49 was obtained by two spraying of Acetamiprid 20% SP @1.0 gm/ liter water during Kharif crop season.

https://www.phytojournal.com/archives/2020/vol9issue3/PartN/9-3-158-356.pdf

Disease management for leaf curl in Chilli

The growth-associated metabolites are produced during the exponential phase; however, this phase terminates due to substrate depletion or product inhibition. In the present study, a semicontinuous mode with a fill-and-draw strategy was applied to extend the exponential phase of the biosurfactant production to overcome the product inhibition and in turn, enhance the yield. Bioreactor studies were performed in batch mode, followed by the semicontinuous operation. A potential biosurfactant producer Bacillus subtilis RSL2 was used in this study at the previously optimized conditions of pH 6.6, temperature 41 °C and 5% (w/v) of molasses. A better mass transfer was achieved in the bioreactor as compared to the shake flask study. In the batch bioreactor study, 90% of sugar was utilized with simultaneous 13.7 g L-1 of biosurfactant production. The sugar utilization was further improved to > 98% in the case of semicontinuous operation employing a fill-and-draw strategy. The exponential phase got extended up to 18 days and a total of 13 L of media was fed in the semicontinuous operation of 21 days as compared to 1.5 L of working volume in the batch reactor. The biosurfactant yield was enhanced by 1.5 folds and was found to be 0.97 g g-1. The produced biosurfactant was identified as a lipopeptide. The interfacial properties of the biosurfactant along with colloidal and thermal stability have been investigated. The critical micelle concentration of the produced biosurfactant was 70 mg L-1. The present study highlighted the efficient utilization of molasses for the production of biosurfactant, an alternative metabolite, in a semicontinuous mode of bioreactor. 

Enhanced production of biosurfactant by Bacillus subtilis RSL2 in semicontinuous bioreactor utilizing molasses as a sole substrate.

Microplastic (MP) pollution has pressing concerns regarding environmental health and the availability of safe food for humans. Information on the occurrence of MP in freshwater biota in the Indian scenario is currently lacking. The present study examined MP contamination in edible and non-edible tissues of widely consumed freshwater fishes. All the fish species (n = 35/species) analyzed had microplastic contamination with the highest MP abundance of 7.86 ± 2.0 items/individual in Channa punctatus followed by Labeo rohita (4.17 ± 0.6 items/individual) and Labeo bata (3.03 ± 0.4 items/individual); whereas MP abundance in small indigenous fishes (SIF) such as Salmostoma bacaila and Puntius amphibius accounts for 0.83 ± 0.13 and 0.77 ± 0.2 items/individual respectively. The principal component analysis results showed a 77.434% variance from two components identified for MP distribution. Fibre type MP was the most dominant type besides fragments and pellets that opined the type of MP required for ecotoxicity assessment, the need of the hour. Raman spectroscopy analysis confirms high-density and low-density polyethylene-type polymers. Evidence of MP in edible tissue indicates the translocation phenomenon resulting in human exposure through the consumption of biota contaminated with MP. Risk assessment revealed a low risk of MP based on its abundance while polymer type indicates a high risk for the fish species investigated. A thorough investigation of the level of adsorbed organic contaminants in the MP is warranted to address the interactive effects on biota. To the best of our knowledge, this is the first detailed report on MP contamination and its risk assessment in Indian freshwater fishes. 

Abundance, characteristics, and risk assessment of microplastics in indigenous freshwater fishes of India.

Arsenic poses a significant threat to both human health and the environment. Arsenic removal through solar oxidation has been investigated in a batch process. Arsenic was artificially added to both deionized and tap water to conduct the experiments. Clean, colorless, transparent, Polyethylene Terephthalate (PET) bottles were used for Solar Oxidation and Removal of Arsenic (SORAS) experiments. Various parameters including concentration of arsenic, iron, and photo-catalyst were varied during the experiments. The maximum arsenic removal efficiency obtained was 94% and 88% for deionized water and tap water respectively when ferrous ammonium sulphate and lemon juice were used. Maximum efficiency of 88% and 82% was obtained for deionized and tap water respectively when locally available ferrous alum and glacial acetic acid were used. The change in volume of the photo-catalyst (lemon juice and glacial acetic acid) also did not affect the SORAS process significantly. Therefore, the recommended volume for the photo-catalyst was 1–2 ml/L. SORAS can very well be used for areas contaminated with arsenic having concentrations less than 100 μg/L. 

Rahul Verma

Papers

Gsm based gas leakage detection system

Disease management for leaf curl in Chilli

Enhanced production of biosurfactant by Bacillus subtilis RSL2 in semicontinuous bioreactor utilizing molasses as a sole substrate.

Abundance, characteristics, and risk assessment of microplastics in indigenous freshwater fishes of India.

Solar oxidation and removal of arsenic from water: An experimental study