Prediction of the Consumption of Electricity for Rural Region

A system which provides prediction of the consumption of electricity for rural region by considering the climatic conditions.

The input parameters of which will be :

Relative Humidity
Wind speed
Max Temperature
Min Temperature
Sunshine hours
Air pressure

The output will be the electricity consumption in kWh for the region (graphical form and numeric value)
Using ANFIS algorithm will be applied on the datasets to obtain estimates of the consumption which will give an estimate of the energy requirements of the area

Platform to be used: MATLAB

The main requirements of prediction of the consumption of electricity for rural regionwill be:
1.Complete training of the data by applying the neuro-fuzzy model
2.The gui with user side page showing options for selecting the month ,year ,region which will
then produce a graph showing the estimated values of electricity consumption along with
comparison with actual values to show accuracy
3.The fuzzy rule set and neural model code. (we have been told by our mentor to avoid to use
any inbuilt functions and code the rule set use in Fuzzy logic and neural network algorithms and
rule sets.)
The user side should be able to login to the system so the gui should also include login page
after which it asks the user to enter the region for which consumption is to be known
5. The application should be able to predict at the electrical load one week and month ahead
6.The coding should be done for feed forward network or bpn for neural part for the given data.
7. Minimum rule sets required for fuzzification of the data for clustering.
8. Output required in charts and numeric value

The basic outline for the neural-fuzzy network.Neural training takes place in the input layer.
10.Minimum tuples required 500-600 for training

Project on IP and Machine Learning using Matlab

Problem Statement

The objective of this work is to develop a system for detection of Alzheimer’s disease from MRI scan of a patient using machine learning approach.

The system will take MRI scan of a patient and will attempt to detect Alzheimer’s based on pre-determined set of features. It will mainly focus on physical characteristics such as texture, area and shape of the hippocampus region which is ill affected in the early stages of the Alzheimer’s.

The output of the system will be a binary classification label suggesting either positive or negative case of Alzheimer’s.

It is basically categorized under neural network matlab based project

Proposed Approach

The proposed approach can be divided into two phases: i) training phase and ii) classification phase

  1. Training phase: A set of labelled MRI scans is pre-processed for noise reduction, normalization, segmentation and ROI extraction. The training phase can be summarized as follows:
  2. Extract features such as texture, mean, skewness, variance, standard deviation, area, perimeter, etc. from the pre-processed MRI scans.
  3. Train an ANN classifier using this feature set.

The output of the training phase is a trained classifier capable of predicting binary classification label based on features of MRI scan.

The performance of the trained classifier can be evaluated using measures like accuracy, sensitivity and specificity.

  1. Classification: This phase can be summarized as follows:
  2. Take as input, MRI scan of a patient.
  3. Pre-process the MRI scan.
  4. Extract the required features from the patient’s MRI scan.
  5. Use the trained classifier to predict the classification label for the patient’s MRI scan.

The output of this phase is a binary classification label suggesting either positive or negative classification label for the patient’s MRI scan.

The metrics used to determine performance of the trained classifier can be used to determine performance of the proposed approach and its comparison with existing methods.

The flowchart in figure 2 depicts the working of the proposed approach.


Object Detection Matlab Project


Object detection is the process of finding instances of real world objects such as faces, vehicles and buildings in images or videos. Face Detection and Pedestrian Detection comes under the Object detection.

Vehicle detection is a part of Object detection. Vehicle detection mainly focus on detecting the vehicle. Automated Vehicle detection will be done by first obtaining the images or videos of vehicles in traffic areas under surveillance. This can be done by using Image Sensors. After the Image or video being captured the vehicles in the image or video have to detected. Finally,after detecting the vehicles the vehicles have to be counted. Depending on the count the traffic volume will be detected.

Automatic Meter Reading System Project Using GPRS

In Automatic meter reading system project using GPRS, we implemented a GPRS Automatic Meter Reading System in order to enhance security for the electrical suppliers in controlling the unauthorized electrical power usage. Web services based GPRS automatic meter reading provides better solutions for the managements in meter reading of power consumptions accurately with no scope man made errors.

The architecture of web services based GPRS automatic meter reading system is designed using microprocessor, Remote Reading Units (RRU), telephone network i.e. Communication Front End (CFE). The meter readings were collected by the remote reading units and transferred to the communication front end systems at the control system and billing is done.

Need of Automatic meter reading systems:

  • In order to prevent the bogus seals and tampering of seals.
  • To reduce Meter tampering, meter tilting, meter interface.
  • To control Meter bypassing.
  • To limit the connection changing’s and Direct tapping from line.

Various Automatic meter reading techniques:

In AMR metering technologies we transmit data from transmitter end to receiver end by means of RF technology.

There are various AMR techniques like handheld computer, touch based AMR, Mobile or Drive-by meter reading, Fixed Network AMR, Radio frequency based AMR, Power Line Communication PLC type AMR system, and Wireless Fidelity (Wi-Fi) based AMR.

Youtube video link cover block diagram , system architecture..etc

Benefits of AMR technologies:

When compared to conventional metering systems automatic metering systems are quite advantageous in terms of  eliminating meter reading costs in manual operations, presenting interference free data transfer from the meter reading units to the billing units, and these are cost effective reliable and free from excess human involvement.

Download Automatic Meter Reading System Project Using GPRS Full Report


The sample model is implemented in a high performance technical computing MATLAB language. The system design is done by SIMULINK software in MATLAB. The process of selecting blocks and initializing them is clearly explained in the coming sections.

Development of color sensor using wireless camera based on MATLAB image processing

The main aim of this Development of color sensor using wireless camera based on MATLAB image  processing project is to develop a color sensor using a camera that can be implemented using MATLAB based Image Processing. Color is the most common feature to distinguish between objects, sorting and recognizing. This technology can be used in Packaging industries where the objects moving through a conveyor belt have to get separated. This system provides such an automatic detecting of specific colored object which presented in front of video camera. The video will be transmitted to the PC. At PC section, this can be seen on PC and further processed through MATLAB. It detects the RGB values of an object that is present in front of Camera.

The video from the camera is transmitted to PC with MATLAB.   The detecting system of object has many advantages such as advanced performance, high reliability, etc. The detection unit reaches the maximum threshold level, this project can be further extended in many ways like can take the photos, displaying pictures, reading and projecting of the data on walls with help of  projector. 

The objectives of the project include: 

  1. Detecting object color by using image processing.
  2. Image processing through PC with MATLAB.
  3. RGB image processing. 

The major building blocks of this project are:

  1. PC with MATLAB
  2. AV transmitter and receiver. 

Software’s used: 

  1. MATLAB. 

Block diagram:


color sensor using wireless camera