Monitoring weather parameters from difficult access places

2019 ◽  
Author(s):  
Gustavo Solano ◽  
Jimmy Tarrillo
Keyword(s):  
Weather Parameters

scholarly journals The correlation between three teleconnections and leptospirosis incidence in the Kandy District, Sri Lanka, 2004–2019

2021 ◽  
Vol 49 (1) ◽  
Author(s):  
N. D. B. Ehelepola ◽  
Kusalika Ariyaratne ◽  
A. M. S. M. C. M. Aththanayake ◽  
Kamalanath Samarakoon ◽  
H. M. Arjuna Thilakarathna
Keyword(s):  
Time Series ◽  
Sri Lanka ◽  
Wavelet Analysis ◽  
Southern Oscillation ◽  
Population Data ◽  
Enso Modoki ◽  
Cross Correlation Analysis ◽  
Teleconnection Indices ◽  
Weather Parameters ◽  
Time Lagged

Abstract Background Leptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI. Methods We acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected. Results Wavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9–11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2–5-month lag periods. Conclusions Results of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

Seasonal Incidence of Pulse Aphid (Aphis craccivora Koch.) and its Natural Enemies on Field Pea (Pisum sativum L.) in Relation to Some Abiotic Factors in Alluvial Zone of West Bengal

2021 ◽  
Author(s):  
S. Pal ◽  
S. Samanta ◽  
A. Banerjee
Keyword(s):  
Relative Humidity ◽  
Pisum Sativum ◽  
Natural Enemies ◽  
West Bengal ◽  
Insect Pests ◽  
Field Pea ◽  
Pest Population ◽  
Pisum Sativum L ◽  
Aphis Craccivora Koch ◽  
Weather Parameters

Background: Field pea, Pisum sativum L. is an important winter-season pulse crop. It is subjected to damage by both field and storage insect pests and approximately 10-15 per cent reduction in yield was reported due to the infestation of different insect pests. Among these, pulse aphid (Aphis craccivora Koch.) affects plant physiology directly by removal of nutrients or indirectly by dispersal of various viral diseases. The present investigation has been aimed to study the seasonal fluctuations of aphids and their natural enemies as well as their correlation. Another objective was to know the effect of various weather parameters on pulse aphids and their natural enemies which ultimately would be helpful to develop a forewarning model.Methods: The field experiment was conducted at the A-B Block Farm of Bidhan Chandra Krishi Viswavidyalaya, Nadia, West Bengal using two varieties of field pea (KPMR 935 and IFPD 122) during rabi seasons of two consecutive years of 2017-18 and 2018-19 following a Randomized Block Design with three replications. After recording the total population of both pests (nymphs and adults) and their natural enemies across the season, the mean population was worked out and used for correlation and regression studies along with the weather parameters. Result: Maximum aphid population was noticed during the peak pod formation stage of the crop irrespective of the varieties. The pest population was very strongly correlated with the incidence of coccinellid and ant population in both test varieties. Among the weather parameters, both maximum and minimum temperature and sunshine hour showed a positive correlation with the pest population and their natural enemies but relative humidity and rainfall showed a negative correlation. Regression studies indicated that temperature and relative humidity were the most influencing factors over the incidence of aphid in both the seasons.

IOT Based Self Vehicle Pollution Checking, Engine Temperature and Fuel Levels with Prediction Alerts

2021 ◽  
Vol 9 (VII) ◽  
pp. 212-220
Author(s):  
G. Naveen Kumar
Keyword(s):  
Internet Of Things ◽  
Atmospheric Pressure ◽  
Geographical Area ◽  
The Internet ◽  
Information Mining ◽  
Simple Idea ◽  
Remote Sensors ◽  
Pollution Detection ◽  
Weather Parameters ◽  
Vehicle Pollution

Pollution detection and ordinary tracking is extraordinarily good-sized errand in this point in time of in our present international. To make a higher and greater steady circumstance for individual, creatures, and plants. We ought to display screen and manage the infection via the Internet of factors innovation. This research proposes air infection and checking version which distinguishes infection in air primarily based totally on statistics mining calculation. The sensor System is used to apprehend the sensor regards from one of a kind fueloline sensors. The microcontroller is applied to trade the features from ADC to server. Information mining is applied to compute the pollution from numerous regions. ID3 set of rules is used to figuring the bottom of the traits on probability. Bluetooth module is applied to interface the controller with the purchaser and the purchaser related to the server via internet administrations. Remote sensors are applied to envision the extent of risky gases gives major all-round that, at last, offers a lower in infection. This framework now no longer simply computes the poisons gift major all-round yet, in addition, we are able to parent to preserve a strategic distance from destiny infection in and might ship the notification message to the particular dirtied location. Here we recall essentially the concoction Industry near Delhi and the metro city groups.These studies paper in particular centered at the evidence of pollutants tracking and locate on precise region or geographical area for an IOT bodily devices that collects statistics with admire to bodily parameters, making use of a complicated microcontroller stage, from one of a kind varieties of sensors, via various techniques of correspondence and after that transfers the statistics to the an internet. The displayed device has been supposed for far flung checking of weather numerous environments. These article facilities across the approach of moving received statistics at the internet with the intention that the device may be applied to remotely display screen weather parameters and in the end take a look at environmental extrade designs like temperature, humidity, Atmospheric Pressure. The paper additionally discusses the simple idea of Internet of Things and its capacity programs, specially for climate tracking.

Sign in / Sign up

Export Citation Format

Share Document