B
bluelinerx
Guest
Global PBS can help save Billions of dollars each year where valuable assets are being damaged or destroyed by harmful pests. We will do this by facilitating “early detection” and early treatment which will stimulate new loss prevention strategies by pest management professionals that will make them better stewards of our environment.
We invented a Polymodal Biological Sensor (PBS)*that can be deployed worldwide to detect the presence of harmful or dangerous pests. Our environmentally green system combines deployed sensor technology, data collection and communications nodes and a target verification program managed by our Global Learning System (GLS).
Our system locates targeted pests within a few feet of a deployed sensor anywhere in the world with a high level of confidence. The system automatically alerts a local pest management professional (PMP) of the pest type and location so appropriate control measures can be taken when needed and at the exact location of the intrusion. This method uses far less pesticides than today’s best method practices (BMP).
Our Technology offers 3 main Benefits:
It identifies pests before they can cause major damage. This Plan considers engineering our sensors to detect pests in several initial markets - further explained herein. However, we are prepared to expand the system to detect nearly “anything” biological.
It greatly reduces the use of pesticides which only need to be used when and where a pest is present.
Our system can anticipate the arrival of pests. The GLS knowledgebase archives can be combined with predictive modeling to forecast arrival of seasonal pests to further mitigate damage.The cornerstone of the system is the Polymodal Biological Sensor (PBS). It’s “polymodal” configuration detects targets using various biometrics; in the scope of this business plan we begin with talking about using methods such as acoustic and chemical signatures. However, many different sensory methods can be employed depending on which is most appropriate for each target. A polymodal sensor is much more effective and reliable that traditional single mode, dual-mode, or multi-mode methods by virtue of the multiple and simultaneous, but different biometric sensory methods.
Our proprietary Global Learning System (GLS) algorithms require that a target be detected by more than one method in a single sensor node (or node-set) to be reported as valid. That “begins” our confidence level for detections at a very high percentage range and the artificial intelligence component of the GLS “learns” not to make the same mistake twice.
The Global Learning System (GLS) includes the operating software, appropriate communications links (e.g. internet, cell towers, land lines, RFID extraction, or LOE satellites). A global knowledgebase archives the detection results from every deployed sensor node - worldwide. It uses historical data in the knowledgebase to make decisions about how to adjust threshold parameters of deployed sensor detections to account for changing climate and other environmental factors thus keeping the system operating at peak performance. A big benefit of our system comes from the GLS by way of automated early detection “notification” to a local pest management professional (PMP) who can quickly tend to the pest intrusion.
Forestry (Mountain Pine Beetles) – Large areas of the American North West and Canadian Pine Forests are being decimated by Mountain Pine beetles. These insects have nearly a year infestation period before the infected trees finally die and reveal the presence of the insects. We propose a sensor that will offer detection “months” earlier than current methods. We have also proposed two additional components for this Project that can “attract” the Beetles to a central location for further management or “steer” them away from high value assets (e.g. City parks and recreation areas). This can save companies (and Governments) money by enhancing current best method practices (BMP) and identify forest stands where beetles have arrived and should be harvested before damage occurs.
We invented a Polymodal Biological Sensor (PBS)*that can be deployed worldwide to detect the presence of harmful or dangerous pests. Our environmentally green system combines deployed sensor technology, data collection and communications nodes and a target verification program managed by our Global Learning System (GLS).
Our system locates targeted pests within a few feet of a deployed sensor anywhere in the world with a high level of confidence. The system automatically alerts a local pest management professional (PMP) of the pest type and location so appropriate control measures can be taken when needed and at the exact location of the intrusion. This method uses far less pesticides than today’s best method practices (BMP).
Our Technology offers 3 main Benefits:
It identifies pests before they can cause major damage. This Plan considers engineering our sensors to detect pests in several initial markets - further explained herein. However, we are prepared to expand the system to detect nearly “anything” biological.
It greatly reduces the use of pesticides which only need to be used when and where a pest is present.
Our system can anticipate the arrival of pests. The GLS knowledgebase archives can be combined with predictive modeling to forecast arrival of seasonal pests to further mitigate damage.The cornerstone of the system is the Polymodal Biological Sensor (PBS). It’s “polymodal” configuration detects targets using various biometrics; in the scope of this business plan we begin with talking about using methods such as acoustic and chemical signatures. However, many different sensory methods can be employed depending on which is most appropriate for each target. A polymodal sensor is much more effective and reliable that traditional single mode, dual-mode, or multi-mode methods by virtue of the multiple and simultaneous, but different biometric sensory methods.
Our proprietary Global Learning System (GLS) algorithms require that a target be detected by more than one method in a single sensor node (or node-set) to be reported as valid. That “begins” our confidence level for detections at a very high percentage range and the artificial intelligence component of the GLS “learns” not to make the same mistake twice.
The Global Learning System (GLS) includes the operating software, appropriate communications links (e.g. internet, cell towers, land lines, RFID extraction, or LOE satellites). A global knowledgebase archives the detection results from every deployed sensor node - worldwide. It uses historical data in the knowledgebase to make decisions about how to adjust threshold parameters of deployed sensor detections to account for changing climate and other environmental factors thus keeping the system operating at peak performance. A big benefit of our system comes from the GLS by way of automated early detection “notification” to a local pest management professional (PMP) who can quickly tend to the pest intrusion.
Forestry (Mountain Pine Beetles) – Large areas of the American North West and Canadian Pine Forests are being decimated by Mountain Pine beetles. These insects have nearly a year infestation period before the infected trees finally die and reveal the presence of the insects. We propose a sensor that will offer detection “months” earlier than current methods. We have also proposed two additional components for this Project that can “attract” the Beetles to a central location for further management or “steer” them away from high value assets (e.g. City parks and recreation areas). This can save companies (and Governments) money by enhancing current best method practices (BMP) and identify forest stands where beetles have arrived and should be harvested before damage occurs.
