mroads taking digitalization to every corner of India

Case Studiesmroads taking digitalization to every corner of India


Forest produce

Collection and sale of forest produce is a great way to monetize forest resources without destroying the forests. This profession is common in areas with major forest covers. "Sangrahaks", who are the tribal farmers, collect wide varieties of forest produce and often sell them to the Government, which processes, packages, and sells them in the retail markets.

Under the project “Sangrahak Survey”, mroads has created a software solution that collects, records, and maintains the data related to these collectors/farmers, ending the use of legacy physical forms. Software is built in such a way that it can collect, and record data in areas where there is no internet connection. In these cases, data is temporarily stored in the browser memory and is transferred to the databases later.

This data can be retrieved by the authorities as and when required. Reports related to any level i.e., Village-wise, District-wise, Union-wise, etc. can be fetched. The purpose of collecting the banking information is to enable digital payments to the Sangrahaks, putting an end to traditional cash-based payments. Data other than banking information is collected and later used to derive insights that aid the decision-making process to frame high-level policies.


We are in a digital era. Data-driven decision-making provides businesses with the capabilities to generate real-time insights and also aids in various types of forecasting. This also holds true with Government policymaking. But, the major problem it faces is in data collection, and analysis. A similar problem is faced while creating databases with information about Sangrahaks.

To build a software solution with huge loads of data being added to it every day, there is always the risk of it crashing. Hence, it needs to be high-performing and stable. Since, this application is used in forest areas, maintaining any physical infrastructure is a challenge. So, it had to be a complete cloud-based architecture with no on-premises components. Since a lot of confidential data is involved; any level of data leakage would be catastrophic. The solution needed to be highly secure & reliable, but also keep the costs low.

This software will also be used in areas where the internet connection could be weak or nil. Hence, the services need to be available as per the conditions. A sudden surge of traffic is expected as the data collectors can upload all the applications on the availability of the internet connection, which can trigger system downtime. To avoid this, the system had to be easily scalable.


As per the requirements, mroads chose to use a complete set of AWS services. The security, flexibility, and cost-effectiveness of AWS make it the most suitable. The system is built on Amazon EC2 architecture which allows elastic web-scaling within minutes without the user waiting days to up/down scale. With the use of Amazon Lambda and its pre-defined functions and tools, users can add custom logic to AWS resources. Since the amount of data is high, Amazon S3 and EBS are used which provides secure storage spaces.

Amazon CloudFront is used to ensure that static and dynamic content is delivered quickly and reliably, without any latency. The system is designed in such a way that it can collect the data and store it temporarily in the browser memory in the absence of internet connectivity. This data would be uploaded in bulk onto the cloud later when the internet connection is available. To handle this traffic surge in peak times, Amazon Autoscaling is used, which observes and automatically adjusts the capacity of the applications. Apart from these, services like Amazon VPC create private networks, As information flow is complex and has several users, user management and authorization service Amazon Cognito is used. The application also uses tools like CloudWatch for monitoring and visualization, Elastic Beanstalk for managing and orchestrating the processes, CloudFormation to model and set the resources.


Services Used

Amazon EC2
Amazon EC2
Amazon Route53
Amazon Route53
Amazon S3
Amazon S3
Amazon CloudFront
Elastic Beanstalk
Elastic Beanstalk


High uptime
Quick scalability
Efficient User management
Secure cloud network
High Data security
Reduction in costs