The project “wisdom of the crowd” was about finding a solution to stealing/loss of individuals in a herd. The solution is based on exclusively manufactured IoT board and an Ad-Hoc wireless network deployment algorithm developed and implemented for it.
The IoT board was based on Lora communication, supports up to 15Km range in open environment, while using minimal energy. The algorithm developed to reduce as much as possible the network traffic and energy consumption, while continue to monitor the location of each individual in the herd.
The project’s goal is to prevent steal/loss of individuals in the herd. To achieve this goal the project was divided into two separate parts. The first part was to design, manufacture and bring up a very low power consumption monitoring device which will be worn by each individual in the herd. The second part was to develop a smart Ad-hoc wireless network deployment algorithm, which will be implemented and tested on the board produced in the first stage.
The whole system will be will be used by farmers and cattle breeders, in order to track the individuals, while consume minimal evolvement by them.
The IoT device which was designed and manufactured is based on Lora communication, supporting long distance range and low power consumption. The system is built with Ultra Low Power (ULP) processor provides high energy utilization. The processor communicates with the transceiver and the GPS unit, and decide whether the individual is safe or not. A high utilization DC2DC convertor was placed to drop the input voltage, and Linear Drop Out (LDO) convertors placed to create more quiet signals in each unit entrance. The system is powered by a rechargeable Lithium battery – charged by a solar panel, and a non-rechargeable battery served for backup. All the power management is done by dedicated hardware.
The algorithm deploys wireless Ad-Hoc network between big numbers of nodes which one of them designated as a root node. The algorithm’s purpose is deploying the network using minimal energy, and minimal network traffic, while continue monitoring all the nodes location and deiced whether one of the nodes disappear from the net – if so, deploy the appropriate part of the net again.
The algorithm was tested in several test scenarios including normal behavior but mostly in ab-normal behavior scenarios which the algorithm should overcome.
The ab-normal test scenarios include: node disappearance, root disappearance, suspicions motion, etc..
