IOT and Data Analytics Solution for Reducing Pollution, Accidents, and Its Impact on Environment

Introduction

The overview by NSW demonstrates that from 2005 to 2013, around 30 individuals are hospitalized by crashes on streets every day. Analysts utilize normal information mining and prediction models on the measure of accident related data. The goal of this paper is to inspect and consider the answer for accidents and reactions to the accidents in the urban zones. Modules have been made to manage the colossal datasets and to bring out interesting bits of knowledge into the outcomes. The module including the assurance of the severity of the accidents, based on specific factors, for example, the city, driving under influence, speed zone, the state of the light and so forth. The above prediction is done by utilizing Decision Tree analysis which produces a decision tree due to prediction.

Consistently, many lives are lost because of accidents, chiefly on the grounds that emergency care fails to reach the accident spot on time. Currently, we totally depend on bystanders to call for help. At times, accidents may happen in remote areas where relying upon human's assistance isn't conceivable. Likewise, the victim may not be in a position to call for emergency vehicle. Considering such circumstances, it would be useful if the way toward distinguishing accidents is computerized.

To robotize the path toward recognizing and reporting accidents, we composed a model, containing System-On-Chip and distinctive sensors in each vehicle. Exactly when an accident happens, the data is sent to the Cloud. This data is used to immediately, advising the concerned specialists, for instance, nearest Ambulance and on the spot medical care.

Air contamination is the presence of particulates, organic atoms, or other unsafe materials in the atmosphere, causing to sicknesses to people or harm to other living life forms i.e. animals and crops, or the natural and manmade structures. Air contamination can be caused because of different human exercises i.e. industries, vehicles and due to the consumption of non-renewable energy sources like wood, coal and so forth or normally. In spite of the fact that there is increment in the advancement of technology and human race, we have neglected the surroundings in which we live in. Along these lines we pollute the nature and thereby lessening the quality of the air in the place we live into. One such significant giver is Motor Vehicles. Roughly 25% of the unsafe gases that are discharged into air are because of internal combustion engine. With the expansion in the quantity of vehicles because of urbanization, air contamination has expanded quickly in the previous couple of years. The essential toxins transmitted from these vehicles are carbon monoxide, oxides of nitrogen and unburned hydrocarbons. CO is thought to be the most harmful among all these. Due to these harmful gases causes different sicknesses i.e. cancer, asthma, Cardiovascular Disease, diabetes, bronchitis and furthermore putting the elderly and the children at a higher hazard. Thus different measures are taken to lessen the vehicular contamination. The variables that add to vehicular contamination are poor fuel quality, old vehicles, insufficient upkeep, old car technology and traffic. Subsequently vehicles that are more fuel efficient and those that create less discharges are a portion of the methods by which we can diminish transport related air contamination. Discharge from vehicles can't be totally reduces, it unquestionably can be controlled.

Rapid industrialization and urbanization have achieved an exponential development of IC engine vehicles everywhere throughout the world and India is no special case. Such developing urbanization, joined with rising number of vehicles, which has led to a new field for exploration regarding traffic analysis, prediction and traffic control. The expansive measure of information accessible today makes information mining strategies to a great degree helpful in rush hour gridlock related research. The work aims for proposing the plan of a model which would address the above issue. Bangalore is the sixth most excruciating city on the planet for traffic jams. The normal speed of private vehicles is 25 km/hr and the speed of public vehicles is 15 km/hr. A 20 km drive in the city can take as long as 3 hours in the peak hours. This Exponential development in the huge number of vehicles and absence of city wide development plan has led to traffic analysis, prediction and traffic control. This undertaking tries to see the traffic video information so as to give an outline of clog level at various intersections over the city. This is done adequately by utilizing data mining strategies