Abstract.Transportation is basic service required by all citizens. Long route transportation is norm today for transporting goods and persons. Road transport has remained one of the important means of transportation. Increase in population and motorization in the country along with expansion of road network contributes to the number of road accidents, injuries and mortalities, as well as loss of productivity. Safety of the passengers, drivers and property is very important issue when we talk about long route travelling. There are many issues that endanger the safety of people and vehicle during long route transportation. Some of them are driver's negligence while driving, overtaking by the vehicles, over speeding of vehicles on the highways, health and mental state of the driver while driving, mechanical issues of the vehicle, sudden arrival of animals on highways, unfamiliar road conditions, negotiating with difficult winding roads, road traffic, overloading of the vehicles and many more. To ensure safety of vehicle and people it is very important to be more cautious and take proper safety measures while driving for long routes. In this research paper we have proposed wireless sensor network based architecture that monitors various parameters that needs to be considered effectively for avoidance of accidents on long routes.
Wireless Sensor Networks produce large amount of data during their lifetime operation. Sometimes this data is in unknown format and bulky. Hence data storage and appropriate mining technique become a critical issue for this domain. Recent innovation in data mining technique receives attention in extracting knowledge from WSNs data. In this paper, we have proposed a Multidimensional Association rule based data mining technique for a cattle health monitoring system based on WSN. We have also given an overview of data mining concept with some selected mining techniques used for WSNs data. We have discussed the different diseases and their symptoms found in cattle. Finally we have proposed a rule based mining technique for identifying the disease based on symptom.
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