Agriculture & Husbandry Solutions based on Ai & ML.
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Automated Farming: Implementing IoT in Agriculture

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As an IT company, we have significant experience in developing sophisticated software and IT solutions for several key sectors. We are recognized as a top California Web Design Agency on DesignRush for a reason.

That’s why we didn’t get puzzled when we started our collaboration with a multinational lighting manufacturer – OSRAM.

The project we came up with is based on IoT technology. Simply put, it’s a software for managing an automated farm.

Since we didn’t have any strong requirements for the project implementation, we conducted research and development that helped to implement a valuable and effective software experience.

So here’s how our solutions look like.

To provide effective implementation of the project, we decided to develop the project with the focus on the final product.

That’s how we chose a “Research and Development” approach for the project’s implementation.

The Research Stage

First things first, we started the implementation of our project with the research step that is the most important stage before the actual development process.

In our company, the research takes 80 percent of all development processes. It’s crucial to start by researching the users’ expectations, before providing any technical research.

As soon as we established the clients’ expectations, we realized that we need to establish the sensor’s communication between each other as well as provide all the necessary conditions for as rapid plant growth as soon as possible.

We invested a considerable amount of time into the research phase in order to fully understand the client’s needs and expectations before heading into the actual software development stage. we evaluated the technology that’s required to fulfill the needs and determine the software-enabled solution that the business is trying to create.

Having collected all the necessary requirements and with a full understanding of what to implement, we arrived to the next step – Ideation. This is where the creative process starts.

During the ideation, we polished all the ideas we came up with. Some of them may be new or revolutionary, others may simply be improvements on the already existing solutions.

Our creative team actively analyzed new ideas and combined them to create a solution that satisfies the customer’s needs and expectations.

The Development Stage

The next key stage – the development stage.

We used Amazon Web Services for building serverless IoT applications that gather, process, analyze, and act on connected device data. At the same time, we don’t have to manage any infrastructure, which reduces costs, increases productivity and innovation.

For an easy test device integration and IoT backend services, we used an IoT Device Simulator solution. This solution provided us with a web-based graphical user interface (GUI) console that enables customers to create and simulate hundreds of virtual connected devices without having to configure and manage physical devices or develop time-consuming scripts.

How Does this Solution Work?

AWS offers a device simulation that allows customers to build a large fleet of virtual widgets from a user-defined template and simulate those widgets publishing data at regular intervals to AWS IoT. Additionally, we could monitor individual widgets from the simulator or observe how backend services are processing the data.

To get a deeper understanding of how it works, let’s take a look at the scheme below:

Image Source

As you can see above, the IoT device simulator consists of the device simulator API that leverages Amazon API Gateway for invoking the solution’s microservice. They can perform operations on virtual devices and device types, record simulation metrics as well as administration tasks.

As soon as device simulator API receives an authorized request, Amazon API Gateway invokes an appropriate Lambda function. This Lambda returns the execution results to the API, which returns the results to the simulator console.

In case if a start simulation request is received, the simulation engine launches a virtual device that starts publishing simulated data to AWS IoT endpoint. After the specific duration, the simulation engine stops the simulation, terminates the virtual device, and updates the device state and metrics in Amazon DynamoDB. A simulation console displays information about virtual devices and device types, simulation states, and user profiles. You use the console to terminate and create virtual devices, start and stop simulations as well as view metrics.

This provides a broad understanding of how this solution works in real life, according to Amazon.

This approach was successfully implemented by us in developing software for automated farming.

A solution that we created allows monitoring environmental parameters in a smart farm. Among the features are managing the temperature, light, water and so on. All the data, which is being managed by the sensors, are transmitted to the cloud. As soon as the cloud has received the data, it transmits everything to the web dashboard that we implemented for farmers.

This allows farmers to monitor the farm condition as well as remotely adjusting the necessary parameters (controlling temperature, for example).

As a result

We successfully implemented a project that was presented on a Consumer Electronic Show and is known as the annual trade show organized by the Consumer Technology Association.

We’re very proud of the fact that we collaborated with such a large corporation as OSRAM and developed a product with rich potential and we also were ranked as top 30 california web design agency of 2019,  and top 40 web design companies in Miami and Florida according to DesignRush.

Here are the potential features:

  • The agriculture sensors allow collecting a huge amount of data, including weather conditions, soil quality, growth progress, environmental changes and so on;
  • Perfect control over the production process as well as maintaining the higher standards of crop quality and growth capacity.
  • Since the sensors can provide information about any anomalies in the crop growth, this creates a possibility of managing and automating the whole farming process.


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