SMART APPLICATION DEVELOPMENT FOR THE RURAL COMMUNITY-c2c-unit-2-ppt.pptx

Smart applications for rural communities harness modern technology to address various challenges and enhance the quality of life in rural areas. These applications leverage advancements in information and communication technology (ICT), the Internet of Things (IoT), and data analytics to improve agriculture, healthcare, education, infrastructure, and overall community well-being. By integrating smart solutions, rural communities can become more sustainable, efficient, and connected.

One of the most significant impacts of smart applications in rural areas is in agriculture. Precision agriculture technologies enable farmers to optimize crop production and resource use. Tools such as soil sensors, weather stations, and GPS-guided equipment provide real-time data that farmers can use to monitor soil health, moisture levels, and crop conditions. Drones equipped with cameras and sensors can survey large tracts of land, identifying areas that need attention and reducing the need for manual inspection. These technologies help increase yields, reduce waste, and minimize the environmental impact of farming practices.

Smart irrigation systems are another critical application, allowing farmers to use water more efficiently. These systems can automatically adjust water delivery based on soil moisture data and weather forecasts, ensuring crops receive the right amount of water at the right time. This not only conserves water but also reduces energy costs and enhances crop health.

In healthcare, telemedicine platforms are transforming access to medical services in rural communities. Residents can consult with healthcare professionals remotely, reducing the need for long-distance travel to urban centers. Wearable health devices and remote monitoring systems enable continuous health tracking, allowing early detection of medical conditions and timely intervention. This is particularly important for managing chronic diseases and providing care to elderly populations in remote areas.

Education in rural communities can also benefit significantly from smart applications. E-learning platforms and digital classrooms make it possible for students to access quality education regardless of their geographic location. Online courses, virtual labs, and interactive learning tools can supplement traditional teaching methods, providing a richer educational experience. Teachers can use these tools to reach a wider audience and offer personalized learning experiences.

Smart infrastructure is another area where rural communities can see substantial improvements. IoT-enabled sensors can monitor the condition of roads, bridges, and other critical infrastructure, providing data that helps with maintenance and repair. Smart grids and renewable energy solutions, such as solar and wind power, can provide reliable and sustainable energy sources, reducing dependence on centralized power systems and improving energy resilience.

Transportation is another sector where smart applications

1. SMART APPLICATION DEVELOPMENT FOR THE RURAL COMMUNITY

2. UNIT-II SOFTWARE DEVELOPMENT PROCESS Software Process Models – Choice of process model - Managing interactive processes – Basics of Software estimation techniques.

3. What is Software? Software is a set of computer programs and associated documentation and data. This is in contrast to hardware, from which the system is built and which actually performs the work.

4. What is Software Engineering? Software engineering is the process of developing, testing and deploying computer applications to solve real-world problems by adhering to a set of engineering principles and best practices.

5. What is software process? A software process is the set of activities and associated outcome that produce a software product.

6. SOFTWARE PROCESS MODEL In software engineering, a software process model is the mechanism of dividing software development work into distinct phases to improve design, product management, and project management. It is also known as a software development life cycle.

7. software engineering models:

8. WATERFALL MODEL

9. software engineering models: V MODEL

10. V MODEL

11. Iterative and Incremental model

12. Iterative and Incremental model

13. PROTOTYPE MODEL

14. PROTOTYPE MODEL

15. SPIRAL MODEL

16. SPIRAL MODEL

17. COMPARISON

18. MANAGEMENT INTERACTIVE PROCESS

19. Managing People Act as project leader Liaison with stakeholders Managing human resources Setting up reporting hierarchy etc.

20. Managing Project Defining and setting up project scope Managing project management activities Monitoring progress and performance Risk analysis at every phase Take necessary step to avoid or come out of problems Act as project spokesperson

21. BASICS OF SOFTWARE ESTIMATION 1.Activities involved in Software Estimation: Projects planning(Estimation determines how much money, effort, resources, and time it will take to build a specific system or product ) 2.Scope and feasibility (The functions and features that are to be delivered to end users.The data that are input to and output from the system.The "content" that is presented to users as a consequence of using the software) 3. Project resources(Each resource is specified with:A description of the resource.A statement of availability,time when the resource will be required.The duration of time that the resource will be applied Time window)

22. 4. Estimation of project cost and effort(The accuracy of a software project estimate is predicated on:The degree to which the planner has properly estimated the size (e.g., KLOC) of the product to be built.The ability to translate the size estimate into human effort, calendar time, and money) 5. Decomposition techniques(Before an estimate can be made and decomposition techniques applied, the planner must Understand the scope of the software to be built Generate an estimate of the software’s size) 6.Empirical estimation models(Estimation models for computer software use empirically derived formulas to predict effort as a function of LOC (line of code) or FP(function point).Resultant values computed for LOC or FP are entered into an estimation model )

23. SOFTWARE ESTIMATION TECHNIQUES

24. SOFTWARE ESTIMATION TECHNIQUES