Monitoring the pulse, heartbeat rate and oxygen levels of a person in an ambulance and then shifting the person to the emergency ward and then continuing the monitoring is what is usually done. The monitoring is stopped when the person is moved from the ambulance and admitted in the emergency ward. This is a big disadvantage because there is a chance of a drop in oxygen or pulse levels at any particular time. We eliminate this disadvantage by installing a pulse sensor, temperature sensor, GPS , pressure sensor, and gas sensor in the stretcher. All these can be connected to a persons body and can be monitored continuously. All these data are displayed on a webpage using IoT. The same stretcher can be used in the emergency ward and the data of the person is not lost at any time period. Using nrf sensors, the ambulance makes communication with the traffic signals located on the ambulances way and makes it turn green until the ambulance passes through it. Therefore the ambulance can reach the hospital soon.

E-Learning development has been a widely adopted methodology nowadays. But there are main risks for learners that they cannot understand in a single stretch of learning. The learning style of every learner varies according to the knowledge and learning object level. Several points have emerged regarding the conception, development and maintenance of E-learning solutions. In our proposed system, Felder Silverman learning style modules had been used to analyze the learner style and the predictive mechanism is enhanced using machine learning methods. The risk of learner will be reduced with the implemented tool. Deep learning can predict the learner style trained labeled data inputs and the tested outputs produce a visualization model of the learner score. The learner scores and the recommendation strategy are added to make learning easier using E-learning technology. Thus the learners can be known as (visual, aural, physical, logical, etc.). This reduces the risk of online learners and the learning objective is well known by the user itself using the implemented methodology. System act as an instructor with the proposed system and an artificial intelligence system is added for a systembased instructor. The statistical test showed that both the behavioral intervention and recommending intervention is based on earlier prediction played a positive role and learning engagement

Removal of ammonium in anoxic conditions with the aid of granulated nanostructured oxyhydroxides of Fe(GNOF) was investigated in sequential batch reactors for biomass with different eco-systems as the source.GNOF was synthesized using a simple template-assisted one-pot technique. The removal of NH4? occurs via a unique short-circuited pathway mediated by a mixed culture of microbes that involves oxidation of ammonium which is coupled to the reduction of Fe3+ along with the formation of N2, NO2 - , and NO3 - . Further, the reduced Fe2+ is oxidized back to Fe3+and hence reducing the amount of GNOF needed to be added to the reactors to ensure the process sustenance. Anoxic removal of NH4? was confirmed from the Enrichment of culture results for 86 days using both aerobic and anaerobic sludge to draw a comparison among the two for their potential to serve as seed biomass. The percentage of removal of NH4? was observed to be 94.65% and 95.07% for aerobic and anaerobic sludge, respectively, indicating both the seed sludges could be used for developing the process. This process is advantageous over the conventional techniques used for NH4? removal as it is more environmentfriendly and economical as less sludge needs to be handled and no aeration is required.

The strength of a nation is in its military powers, including soldiers in air, water, and land. To monitor such soldiers, a small and efficient system is proposed. This system is mountable to the soldier and monitors the health parameters and location of the soldier. Some useful to the soldier are also incorporated into this system, which includes metal detection for landmines and the ability to send an SOS signal to the control room. The implementation of the LoRa (Long Range) technique helps us to transmit the signals from the soldier to the control room with a low data rate, at long distances. By using LoRa we can make a system that is better at consuming low power and transmit at a high transmission power. The health monitoring system comprises of heart rate monitoring, pulse monitoring, temperature measurement, and motion detection. Motion detection helps in the identification of the fatigue levels of the soldier in the war zone. Metal detection is assisted by the use of an Inductive proximity sensor. These combinations of devices help in the effective tracking of the soldier in the field and their parameters, thus contributing to the individuals increased survivability

This research study is expected to set up an early screening model to detect Novel Coronavirus (2019 – nCov) Pneumonia, with aspiratory CT scan utilizing Digital Image Processing procedures. The signs of registered tomography (CT) imaging of 2019 – nCov had their attributes, which are not the same as different sorts of viral Pneumonia. Accordingly, clinical specialists require another early analytic criterion for this new kind of Pneumonia at the earliest opportunity. The applicant contamination locales were handled under Digital Image Processing systems: image preprocessing, image enhancement and image segmentation of a 3-dimensional pneumonic CT image set capturing. These isolated images were then sorted into 2019 – nCov, using a marker-based watershed segmentation method

The distribution system reliability assessment deals with availability and quality of power supply at each customer service entrance. This paper focuses the assessment of power distribution reliability of Addis Ababa city which is connected from Cotebie distribution substation and the possibility of using smart reclosers and disconnectors to mitigate the urgent and pressing power interruption problems. Depending of the assessment result Cotebie distribution substation has reliability indices such as average frequency of interruption is 133.37 interruptions per year per customer and the average interruption duration is 187.31 hours per year per customer. This value shows the substation has greater reliability problems and the substation does not meet the requirements set by the regulatory body that is Ethiopian Electric Authority (EEA). In this paper, the reliability is improved in to 22.27 interruptions per year per customer average frequency of interruption and the average interruption duration is 31.274 hours per year per customer. It can also improve above this value depending of the segment and recloser number. The designed system is simulated using WindMil software that is used to analyze the reliability of the overall system. The simulation of the designed model shows that the application of smart reclosers and disconnector coordination can improve the reliability from 50% up to 83.3%.