Global Statistical Study of Ionospheric Waves Based on COSMIC GPS Radio Occultation Data

Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we calculate the parameters of ionospheric waves by applying the MMEM to numerously temporally approximate and spatially close global-positioning-system radio occultation total electron content profile triples provided by the unique clustered satellites flight between years 2006 and 2007 right after the constellation observing system for meteorology, ionosphere, and climate（COSMIC） mission launch. The results show that the amplitude of ionospheric waves increases at the low and high latitudes（~0.15 TECU） and decreases in the mid-latitudes（~0.05 TECU）. The vertical wavelength of the ionospheric waves increases in the mid-latitudes（e.g., ~50 km at altitudes of 200–250 km） and decreases at the low and high latitudes（e.g., ~35 km at altitudes of 200–250 km）.The horizontal wavelength shows a similar result（e.g., ~1400 km in the mid-latitudes and ~800 km at the low and high latitudes）.

Traffic Data： Bluetooth Sensors vs. Crowdsourcing——A Comparative Study to Calculate Travel Time Reliability in Calgary, Alberta, Canada

The City of Calgary did a comparative study between two techniques of traffic data collection： Bluetooth sensors and crowdsourcing, for measuring travel time reliability on two goods movement corridors in Calgary, Alberta. To estimate travel time and speed, we used the output of BIuFAX sensors, which were operated by monitoring Bluetooth signals at several points along a roadway. On the other hand, TomTom historical traffic data were extracted from the TomTom Traffic Stats portal. To calculate travel time reliability, we applied the buffer index, and the planning time index recommended by FHWA （Federal Highway Administration）. The Bluetooth traffic data were presumed as the benchmark in this study. Unlike the TomTom traffic data, the data provided by the Bluetooth technology met the minimum recommended sample size requirement, although data processing was time consuming and impractical for long study periods. Our study results showed that crowdsourcing technique can be a viable alternative and provide travel time reliability estimates with a reasonable accuracy, when there are adequate numbers of records registered. However, the TomTom sample sizes in Calgary were not large enough to provide a statistically reliable method of providing travel time indices. Further researches may verify the accuracy of crowdsourcing technologies for travel time studies.

An internet of things assisted drone based approach to reduce rapid spread of COVID-19

With the quick spread of pandemic disease,many individuals have lost their lives across different parts of the world.So,the need for a novel approach or model to overcome the problem becomes a necessity.In this paper,a mechanism is proposed called DBCMS(Drone Based Covid-19 Medical Service)for the safety of medical em-ployees who are prone to Covid-19 infection.The proposed mechanism can effectively improve the treatment process of Covid-19 patients.Drones are nowadays commonly used in the field of medical emergency situations.The proposed model in this paper uses drone service to reduce the risk of infection to the doctors or other medical staff,thereby preventing the disease spread.This paper further assumes that the primary step is to isolate people at their home instead of admitting them to the hospitals,also called a situation of lockdown or curfew.Thus,in this way,the spread can be significantly reduced across the globe if DBCMS approach is implemented at cluster level.