System, method, and apparatus for active pest denial, apiary monitoring and management

A system for identifying and actively denying pests entry to a beehive, the beehive comprising at least a brood box with an entrance for access, the system comprising:

• one or more visual classification sensors configured to collect real-time data and classify insects attempting to enter the beehive by monitoring a dorsal view of the entrance of the beehive;
• one or more audio classification sensors positioned near the brood box entrance, configured to collect real-time audio data and classify insects attempting to enter the beehive by monitoring ambient sounds for insect classification based on flight pattern sounds, wingbeat frequency, and spectral signature analysis;
• an apparatus configured to mount on a brood box of the beehive said apparatus comprising means for mounting the one or more visual classification sensors and the one or more audio classification sensors and for restricting entry to individual entry points that are monitored with the one or more visual classification sensors;
• a classification and control computer configured to process data collected by the one or more visual classification sensors and the one or more audio classification sensors using specialized classification algorithms, including traditional algorithms and machine learning-based classification models, to establish an identity of the insects in real-time based on factors including size, sound, shape, speed, coloration, and direction of movement;
• a user interface for declaring a beehive species upon initialization of the classification and control computer, wherein a user selects either Apis cerana, or Apis mellifera, or another desirable honeybee species as a target beehive species, and with all other bee species being considered pests and excluded from the beehive;
• a processing module for selecting a library of images and audio files typical for the declared species for positive training of the neural network, as well as a library of images and audio files of pests for negative training of a neural network-based inference algorithm specific to the selected honeybee species, wherein a pre-generated inference data set was previously generated during training using a library of images and audio files representative of the declared species for positive training, and further includes data trained using a library of images and audio files of pests, including wasps, beetles, mites, wax moths, Braula flies, spiders, earwigs, ants, cockroaches, and mite-infested bees, and wherein the inference data set may also incorporate audio files of bees under normal conditions and under stress;
• one or more automated kill mechanisms positioned at each entry point of the beehive, wherein each kill mechanism, under the control of the classification and control computer, is activated only at the specific entry point where a pest is identified, ensuring that non-target insects, including bees at other entry points, remain unaffected, said one or more automated kill mechanisms being configured to prevent pest entry based on classifications determined by the classification and control computer;
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• a secure communication interface configured to provide authorized users with access to statistics related to insect classifications, notifications of limit conditions, and user-defined thresholds for specific insect types, the system comprising multiple communication links, including but not limited to local area networks (LAN) and wide area networks (WAN), wherein the system provides;
• access to real-time and historical statistics related to insect classifications;
• automated notifications of limit conditions, colony stress, or hive intrusion;
• threshold settings defined by the user for specific insect types, allowing the user to customize exclusion parameters;
• adaptive data transmission, wherein LAN-based communication is used when an authorized user is nearby, and WAN-based communication is utilized for remote monitoring;
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• integration with external databases or regulatory agencies for epizootiological tracking and regional pest monitoring.