AgriSciense's Latest Milestone : Advancing to field testing

Greetings from AgriSciense! We are thrilled to share our latest progress in tackling the persistent challenge of pest management in agriculture. We are committed to developing innovative solutions that empower farmers to detect and mitigate pest infestations at an early stage, thereby safeguarding their crops and livelihoods.

In our previous blog post, we outlined our approach to addressing the threat of pests, particularly focusing on the detection of the red-palm weevil insect in date palm trees. Today, I am delighted to provide an update on our journey as we move closer to performing our proof of concept (POC) in real-world agricultural settings.

Enhancing Hardware for Optimal Performance

At AgriSciense, we recognize the critical role that hardware plays in the effectiveness of our pest detection solution. Therefore, we have been diligently fine-tuning our first version of hardware to ensure optimal performance during our upcoming POC on pilot farms. One significant enhancement we have made is the integration of an amplifier into our hardware design. This amplifier amplifies the vibrations emanating from the trees, enhancing our device's sensitivity and accuracy in detecting pest activity.

Technical Specifications and Capabilities

Our latest hardware iteration boasts impressive technical specifications, including a frequency range of 0.5-8kHz and a sensitivity of 25mV/g. These specifications enable our device to capture a wide range of vibrations associated with pest activity, ensuring comprehensive coverage and detection accuracy. Moreover, powered by a battery, our device can operate continuously for a week, providing uninterrupted monitoring and data collection. Looking ahead, we are excited about the prospect of incorporating solar capability into future versions of our hardware, enhancing sustainability and longevity.

Data Collection and Analysis

In operation, our hardware device wakes up every five minutes to capture vibrations within the trees. These raw data are then converted into WAV files and transmitted to our cloud server for analysis. Leveraging our advanced machine learning algorithms, we will assess the accuracy of our model in detecting pest infestations based on the captured data. This iterative process of data collection, analysis, and refinement is crucial to ensuring the reliability and effectiveness of our solution in real-world agricultural environments.

Looking Forward: Field Testing and Continuous Improvement

As we prepare to deploy our POC hardware device to farms, we are eager to gain valuable insights and feedback from farmers and agricultural experts. This field testing phase not only allows us to validate the performance of our hardware and software but also provides an opportunity to iterate and improve upon our solution based on real-world usage and feedback. We are committed to transparency and collaboration throughout this process, and we invite you to stay tuned for further updates and insights.

In conclusion, AgriSciense is making big progress. We will keep you updated with the progress. We are more than happy to have a chat, feel free to reach out to us.