This paper presents a forecasting model designed using WSNs (Wireless Sensor Networks) to predict flood in rivers using simple and fast calculations to provide real-time results and save the lives of people who may be affected by the flood. Our prediction model uses multiple variable robust linear regression which is easy to understand and simple and cost effective in implementation, is speed efficient, but has low resource utilization and yet provides real time predictions with reliable accuracy, thus having features which are desirable in any real world algorithm. Our prediction model is independent of the number of parameters, i.e. any number of parameters may be added or removed based on the on-site requirements. When the water level rises, we represent it using a polynomial whose nature is used to determine if the water level may exceed the flood line in the near future. We compare our work with a contemporary algorithm to demonstrate our improvements over it. Then we present our simulation results for the predicted water level compared to the actual water level.

A Simple Flood Forecasting Scheme Using Wireless Sensor Networks

A constraint is defined as a logical relation among several unknown quantities or variables, each taking a value in a given domain. Constraint Programming (CP) is an emergent field in operations research. Constraint programming is based on feasibility which means finding a feasible solution rather than optimization which means finding an optimal solution and focuses on the constraints and variables domain rather than the objective functions. While defining a set of constraints, this may seem a simple way to model a real-world problem but finding a good model that works well with a chosen solver is not that easy. A model could be very hard to solve if it is poorly chosen.

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A Review of Constraint Programming

A logical relation among several unknown variables is known as a constraint, where each variable in a given domain takes a value. The basic idea behind constraint programming framework is to model the problem as a set of variables with domains and a set of constraints.This problem has been studied since 1897 i.e. more than a century. In this paper we will consider a problem which will represent the basic features of constraint programming. We will here use constraint programming to solve this problem of knapsack. Our goal is to select items which have a greatest total value under certain conditions of limit on weight.

Vaishali Cooner

Papers

A Review of Constraint Programming

Solving Knapsack Problem Using Constraint Programming