Software Products & Systems

Campus Placement Software System

A web based software for colleges to improve their placement performance by automating the placement activities. Campus Placement system is customized for a college, which helps to communicate with administration, faculty and students. This system allows the admin to add the faculty and students, giving them their user id and password provided by them in their details. This system keeps a track of the company coming to the campus, number of students who can apply in the company, number of students who got selected in the company and the whole list is then forwarded to the respective department faculty members. The details of the company is uploaded by the admin, the faculty and the students can view the changes uploaded. The faculty member and students gets email and SMS notification of the job profile uploaded for their department.

FingerPrint Attendance System For Classes & Tutions

Fingerprint attendance system for classes uses biometric of the batch of students attending the lectures in the specified venue with a specific time duration (in hours or day). Fingerprint attendance desktop software, lessens the burden of the management of the classes by manually taking attendance of the students. This system allows the admin to add the students with his details provided while enrolling to the classes. Depending on the availability in the batches the students are assigned to the particular batch. Fingerprint attendance desktop software keeps the records of the student's attendance and notifies them as well as the faculty about the defaulters list, i.e., student who don't regularly attend the lectures. The students has to scan their finger as they enter the premises and while leaving the premises of the classes.
This software hence improves the whole attendance system making it easier for the administration to keep the records and managing the updates with very little efforts.

Super Market Billing System

Super market billing system, is a software developed for super markets. It allows two logins, Admin and the employee. The admin add the product details to the system, as well as assigns the barcode. The admin login allows to update stocks to the inventory and keeps a record for updating the new stocks. He/she is given access to add any employee to the database. The admin can add the employee, view or edit the employee details, and delete the employees from the database. The report are generated by the admin login. Daily, weekly, monthly or yearly sales report can be generated by the admin. They can even view and edit and generate a product and purchase report on the daily, weekly or monthly basis. Employee daily report is also anther function the admin can access. Once the admin gives the login details to employee, he can login to generate the purchase bill. The employee can scan the product, update the quantity, delete the product if the customer changes mind at the last moment, avail any coupon and print the bill. With the employee login, they can view the bills generated. The admin has all the authority compared to that of the employee login.

Chatbot & Personal Assistant Development Service

This is the era of AI systems. Automate your business with chatbots that handle thousands of customer at a time, provide 24/7 support to customer queries and provide personalized chat experience to every customer. Save time and money by letting a single chatbot handle all your customer queries which would otherwise require a lot of manpower.

RFID Attendance System With SMS For Schools Colleges

Traditional attendance systems requiring manual attendance and calling are now slowly becoming history. Get along the latest attendance technology that does not even need user to scan a card. Just walk through and the attendance is marked. These systems use RFID attendance scanners to be mounted in schools, colleges and university entry/exit gates or classrooms for automated attendance markings.
NevonSolutions brings you a whole range of advanced RFID based attendance solution to automate the entire attendance process. This is coupled with SMS notifications to respective parents about their child reaching the school on time and leaving time. This RFID attendance system for schools and colleges/universities is automating attendance processes all over the globe.
NevonSolutions introduces state of the art RFID based attendance systems for schools to help automate their attendance procedure within days. Our easy to install offline systems are easy to use and have no recurring costs. We also provide full offline RFID based attendance systems with SMS notifications that require no internet and no recurring costs every year.

IOT App Development Services & Solutions Provider India

The Internet of Things is quickly changing the way India operates and how devices collect and transmit data via the internet. Unless you stay ahead of trends you are not keeping up and will be left behind by your competition. What would you do if you could turn your ideas into real-life active applications that your customers will love and keep them loyal to you? What would it be worth to you to have IOT development services in India that were just a click away and could bring all your technological IOT ambitions to life ?

NevonSolutions introduced IOT development services in India to help various sectors upgrade and adapt IOT based solutions for better productivity. We offer a number of customized IOT solutions for various sectors in India.

GPS School Bus Tracking System With App

A school has to bear the responsibility for safety and security of all students in it. But managing the safety of such large number of students becomes quite a difficult task for the school management. To help schools ensure the safety as well as to help parents track their child movement as well as track school bus as to where it has reached, nevonsolutions introduced an advanced school bus tracking system. The system uses GPS as well as rfid technology in order to track student movement as well as bus position for safety and advanced tracking to help parents as well as school management. This system automates the entire school bus tracking process and alerts parents as well as school authorities about all details.

Artificial Intelligence in Trade Promotions

Trade promotion is a marketing technique which provides several benefits to businesses. Many companies use trade promotions to increase distribution of their product at retailers and build strong relationship with retailers. The main objective of implementing artificial intelligence in trade promotion is to increase demand for products in retail stores. Artificial Intelligence has been used in modeling consumer choices. Here we proposed artificial intelligence for marketing products by predicting consumer choices. Consumer choices are decided based on the consumer purchasing behavior toward goods and services involves a five stage which includes problem recognition, search, evaluation of alternatives, choice and outcome. Trade promotion is a process that requires identifying group of consumers described by a set of similar characteristics, in order to improve marketing activities through a better allocation of resources and formulation of customizable strategies. Consumer behavior can be identified by using artificial intelligence techniques such as artificial neural networks(ANNs). Artificial intelligence techniques are statistical data modeling techniques in which interconnected elements (called nodes) process simultaneously the information, adapting and learning. The main purpose of this study is to analyze result obtained when building Artificial Intelligence model that identifies individual with great chance of purchasing products, using artificial neural networks. Artificial neural networks are non-parametric methods used for pattern recognition of consumer purchase behavior and optimization. Artificial Intelligence in trade promotion provides new strategies, tactics and technology choices to maximize trade promotion spend by anticipating demand and predicting revenue, volume and profitability. Modeling data with artificial neural networks allows a flexible approach towards independent variables. For trade promotion analysis a multilayer perceptron was used to model consumer data. The ability to enable trade promotion is a fundamental aspect to success for any business. Trading promotions using Artificial Intelligence provide best approaches, strengths and best application to businesses.

Objectives

  • To increase sales of new products and services
  • To increase sales of traditional products and services
  • To increase inbound customer leads
  • To enhance customer satisfaction
  • To generate new insights and better analysis
  • To increase operational analysis
  • Demand Forecasting Using Artificial Intelligence

    In the latest generation of products, artificial intelligence is adding intelligence pretty much everywhere you look. Future demand of product or a service is predicted based on the past events and prevailing trends in the present. To get accurate sales forecasts in a supply chain is certainly an important key. If the future demand is predicted accurately it will affect other productivity factor such as planning, performance and profit of product. In this study we had researched on effective artificial intelligence models to predict demand of customer's product. For forecasting demand, we require good historical data. These data are required for training and validating data. Tools are needed to take advantage of it. Artificial intelligence that allows the computer to “learn” from data. We will predict demand by implementing best artificial intelligence algorithm. Algorithm will focus on finding the optimal structure for demand forecasting. When it comes to demand forecasting, artificial intelligence can be especially helpful in complex scenarios, allowing planners to do a much better job of forecasting difficult situations. It leverages the knowledge, experience, and skills of planners and other experts in a highly efficient and effective way across a broad range of data. The main contribution of our work is the use of artificial intelligence models in order to predict the consumer's demand and implement this demand forecasting in a two-echelon supply chain with a game theoretic approach. .

    Objectives

  • To improve product forecasts and demand plans
  • To allow collaboration between all departments involved in demand planning
  • To provide accurate demand forecast
  • To provide accurate cost / benefit analysis
  • To increase profitability
  • Heart Attack Prediction Using Artificial Intelligence

    The World Health Organization (WHO) has estimated that 12 million deaths occur worldwide, every year due to the heart disease. About 25% deaths in the age group of 25-69 year occur because of heart diseases. In urban areas, 32.8% deaths occur because of heart ailments, while this percentage in rural areas is 22.9. Over 80% of deaths in world are because of Heart disease. World Health Organization estimated by 2030, almost 23.6 million people will die due to Heart disease. Our research is to detect heart attack using Artificial Intelligence(AI) based on heartbeat, pulse rate and blood pressure in order to reduce death rate due to heart attack. There are several ways doctor can predict heart disease based on the parameters such as cholesterol levels, blood pressure, blood glucose levels and weight. We are trying to develop a method that will optimized to use less conventional equipment's as much as possible but also maintain the accuracy of detection. We are trying to avoid conventional methods as they are time consuming but we are trying to detect the heart attack pain as soon as possible so that the patient can have enough time to react. Here we come up with new methodology where heart attack can be predicted based on parameters such as pulse rate, heartbeat and blood pressure. Our Heart condition can be measured by important vital signs such as heart beat and pulse rate. People whose pulse rate creped from under 70 beats per minute at the first reading to more than 85 beats per minute at the second measurement were in critical condition. People who started out pulse rates between 70 and 85 beats per minute were also at risk of heart-related death; if their heart rates rose beyond 85 beats per minute by the second reading, they had an 80% increased risk of dying from heart disease, compared with people whose heart rates remained stable. Experts say healthy adults can have pulse rates ranging from 60 to 100 beats per minute. Elite athletes typically have lower heart rates, around 40 beats per minute because of their better heart fitness. The main purpose of this paper is to build a heart rate prediction model, which is based on real-life heart rate. Here we use Artificial Intelligence (AI) algorithms to train data and search for patterns and can build internal guidelines. Here we will use sensor to check heart rate of a person based on the heart rate, system will predict heart attack based on parameters such as pulse rate, heart beat and blood pressure.

    New Product Launch Using Artificial Intelligence

    A very important activity for companies is launching a new product which is very risky process due to the uncertainty degree encountered at every development stage. To overcome this uncertainty there is need to evaluate new product initiatives systematically and make accurate decisions under uncertainty. Here we propose an integrated decision-making application based on Artificial Intelligence techniques to make appropriate decisions and accelerate new product launch. We come up with an intelligent approach that allow practitioners to roughly and quickly experience and analyze product ideas by making use of previous experiences. Here we collect high quality resources to create new product. We use Artificial Intelligence techniques to accelerate the new product development while taking into account the uncertainty factors that affect product development. There are various Artificial Intelligence techniques. Here research is aimed at studying Artificial Neural Network to predict the chance of success in new product launch. Artificial Neural Network is model of reasoning based on human brain. It was developed to solve problem with unknown pattern, insufficient or uncertain data by resembling the learning and working process of human brain. The analysis is conducted by using the Feed-forward neural network with back propagation technique. We researched that Artificial Neural Network technique has sufficient ability to predict the success of new product launch. The accuracy of results is affected by a number of factors such as the number of available data relative to the variables of interest, the quality of data from the questionnaire. We get input data from the questionnaire which are scaled to a range. Trained data is normalized and presented to the neural network to predict value. The predicted value is compared with the target value to measure the success of product launch. In this study we had used network training function in order to minimize the effect of training parameter setting. Here we researched to explore the relationship between new product launch success factors by adopting Artificial Intelligence. Artificial Intelligence techniques is used to predict new product launch success in various dimensions. The result provides a general guideline for firms wishing to forecast the chance of success on their new products.

    Objectives

  • To accelerate new product launch
  • To enhance old product quality
  • To improve uncertainty occurred during development stage
  • Helps to forecast chance of success of their new products
  • To achieve high percentage of accuracy
  • Predicting Weather Data Using Artificial Intelligence

    Predicting accurate weather condition is vital for many reasons in multiple areas such as agriculture, energy supply, transportations etc. Here we come up with a technique by combining whether forecast with artificial intelligence. There are multiple artificial intelligence techniques to identify and predicting climatic condition with certain accuracy which are used for multiple purpose. For weather forecast there are Artificial Intelligence techniques such as Artificial Neural Network, Ensemble Neural Network, Backpropagation Network, Radial Basis Function Network, General Regression Neural Network, Genetic Algorithm, Multilayer Perceptron, Fuzzy clustering, etc. In this study we found neural network with backpropagation algorithm with minimal error. We explore new directions with forecasting weather as a data intensive challenge that involves inferences across space and time. We introduce methods that show promise for advancing the state of the art of weather forecasting systems. In this technique we use multiple input parameters to forecast weather based on terms such as temperature, rainfall, humidity, cloud condition, and weather of the day. Now-a-days many live systems depend on weather conditions to make necessary adjustments in their systems. In this study we focused on Artificial Neural Networks to forecast the weather. An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected processing elements (neurons) working in unison to solve specific problems. An Artificial Neural Network is configured for a specific application, such as pattern recognition or data classification, through a learning process. In this study we had proposed Artificial Neural Network with backpropagation algorithm for forecasting weather accurately. Accuracy is vital in weather forecasting. The input parameters must be handled based on the Artificial Intelligence technique. Artificial Intelligence is associated with non-linear data.Artificial Neural Network technique uses an iterative process of training data and repeatedly compares the observed output with targeted output and calculate the error. This error is used to readjust the values of weights and bias to get an even better output. Hence this method tries to minimize the error and provides accurate whether forecast.

    Objectives

  • To get accurate weather forecast
  • To minimize the error
  • Analyze pattern to generate weather forecast
  • To be used in multiple areas
  • To be associated with non-separable data
  • Study on Machine Intelligence to Predict Health Issues

    Here we come with an idea to use Artificial Intelligence to detect health issues in human body based on certain variables. This System can definitely assist physicians to make better clinical decisions or even replace human judgement in certain functional areas. This system can be utilized to predict various health issues such as heart disease, diabetes, head-ache, depression and anxiety. The main objective of this system is to predict multiple disease. We had done deep research to predict multiple heath issues with different health parameters. The unique idea is to predict multiple health issues by using one product. In Artificial Intelligence, it is necessary to learn features from large volume of health-related data. We apply sophisticated Artificial Intelligence algorithm to work on large data and to obtain insights to assist clinical practice. The system extracts useful information from a large patient data to assist in making real-time inferences for health issue alert. Here we researched artificial intelligence techniques that extracts information from unstructured data generated from medical reports. In this study, data need to be trained that are generated from clinical reports such as screening, diagnosis, treatment assignment etc. Data Analytical algorithms used to extract pattern from data. Input data will be patient medical report or disease specific data such as EP test, Physical examination results, clinical symptoms, medication and so on. There are many Artificial Intelligence algorithm here we use Artificial Neural Network methodology. In this study we implemented Artificial Neural Network to predict health risk with minimal error. In neural network, the associations between the outcome and the input variables are depicted through multiple hidden layer combinations of prespecified functionals. The goal is to estimate the weights through input and outcome data so that the average error between the outcome and their predictions is minimized. Artificial Intelligence system helps physicians to make clinical decision points.

    Objectives

  • To extract information from unstructured data
  • To predict health risk with minimal error
  • To predict multiple disease
  • To make real-time inferences
  • To learn features from large volume of data
  • Bus Booking & Management System Software

    Ensure efficient bus seat utilization saving on fuel costs and ensuring easy seat booking by your bus passengers. Nevon Bus booking system ensures the best bus service utilization for you as well as the passengers. With android and iOS apps for ease of booking allows passengers to see all bus schedules and book available seats from the comfort of their home. Admin reports give you in insight into bus seat utilization to see areas of improvement, improve passenger comfort as well as save on fuel costs and optimize bus utilization efficiency.

    Clinic Appointment Scheduling & Coordinator System

    This Android app system helps doctors manage other visiting doctors, colleagues in their clinic/hospital as well as manage and maintain patient data. This automates many activities including appointment booking, patient records storage and retrieval, manage visiting doctor schedule and appointments and more.

    Clinic Appointment Scheduling & Coordinator System

    This Android app system helps doctors manage other visiting doctors, colleagues in their clinic/hospital as well as manage and maintain patient data. This automates many activities including appointment booking, patient records storage and retrieval, manage visiting doctor schedule and appointments and more.