Tech Solutions
Our core Intellectual Property
At Entoverse, our core intellectual property revolves around leveraging Big Data and Artificial Intelligence (AI) to forecast yields and recognize emerging trends.
AI operates on the premise of data. Big Data represents expansive datasets utilized for this specific purpose, uncovering intricate patterns and trends and enabling accurate predictions for the future.
AP disciplines
1. Machine Learning
This field centers on crafting software capable of learning from data and applying that acquired knowledge to process new datasets.
2. Deep Learning
Our expertise includes designing neural networks that emulate the human brain’s functionality, enabling the processing of complex data such as sounds and images.
Management technologies
Audio recognition
AI and machine learning techniques, such as deep learning and neural networks, are integral in speech recognition software. These systems meticulously analyze grammar, structure, syntax, and audio composition to comprehend spoken language.
Insects communicate through their distinct sounds, like chirping, utilizing volume, frequency, and periodicity parameters. Leveraging these particular sound elements, audio recognition systems prove to be both suitable and valuable for insects. This technology aids in swiftly identifying abnormalities in cricket chirping, enabling prompt actions based on the underlying causes of irregularities.
Video recognition
AI isn’t only useful for sound analysis. It’s also applicable for recognizing human actions. If we can identify human actions, why not monitor insects’ behavior? Detecting problems in insects’ conditions can be time-consuming, and undetected diseases at early stages can lead to colony losses. Our system is trained to detect and classify abnormal insect behavior throughout their entire lifecycle, providing actionable recommendations.
IOT
IoT (Internet of Things) reduces human labor in data collection. Automatic sensors send data directly to our system, making data collection less labor-intensive and saving significant time by eliminating manual work.
QSAR
Quantitative Structure-Activity Relationship (QSAR) is a computational modeling method that reveals relationships between chemical compound structures and biological activities. QSAR modeling is crucial in developing organic biohack additives. Tailoring additives to specific farms is essential due to varying conditions, feed types, and technological processes. QSAR helps generate customized recipes suited to each farm’s unique requirements.
ERP System
Our system simplifies farm monitoring by consolidating data from various sources into a single platform. It efficiently collects sensor information and enables workers to input necessary data via a chatbot interface. The ERP system also ensures essential notifications and reminders, preventing the loss of vital data.
Technologies
Our technology encompasses extracting and analyzing information from audio and video sources. These processes involve classifying, storing, and retrieving data, enabling automatic identification of factors like gender and illness in insects. Overall, it aids in detecting various abnormalities within the farming environment.
When combined with sensors, our system offers 24/7 control and farm monitoring, accessible remotely via mobile phones or PCs. It provides real-time access to parameters, alerts, task lists for workers, and critical situations, allowing farm owners to stay connected and manage operations even when physically away from the farm.