Will your next hotel stay be their last? Bed Bug Detector is the tool you need to inspect hotels, motels and other lodging for bed bugs. This tool provides you with a checklist of places to look for and signs you should look for when inspecting for bed bugs. I’ve been bitten more than once by these little pests, but I’ve been able to find them before they had a chance to reproduce.  With this simple, yet effective tool, you will be able to inspect any room or area with relative ease, making sure that bed bugs are the only thing you take home after your next stay. Are you tired of sending potential business away because they’re afraid of bringing bed bugs home with them? Or maybe you’ve hear horror stories about people who get bed bugs and wish you could avoid that situation. If so, Bed Bug Detector is for you!

Bed Bug Detector

The rationale behind our idea is to have a self-contained device that can detect the presence of bed bugs in your mattress by using temperature.

The rationale behind our idea is to have a self-contained device that can detect the presence of bed bugs in your mattress by using temperature. Bed bugs hide in mattresses and are usually found in the seams of the mattress, making them hard to detect with the naked eye. They are cold blooded and are heat sensitive, making thermal imaging an ideal method for detection.

Our solution is to use a thermocouple to get the temperature of the bed and run the data through a neural network.

Our solution is to use a thermocouple to get the temperature of the bed, and run the data through a neural network. The neural network will then compare this data with known patterns for bed bugs, and determine whether or not there are any in your mattress.

This will require us to collect enough data in order to accurately train the network and identify bed bugs.

In order to train the network, we need a dataset of images that have already been labeled. To do this, we will be using a dataset from Open Images. This dataset consists of over 8,000 images that have been manually labeled by humans (they were actually paid an hourly wage). It is important that our training data has both images and temperature data associated with each image.

The first step in training your neural network is to find or create a dataset of bed bugs with temperature data attached. If you can’t find one online then you will have to collect your own data by taking photos and recording temperatures at home while bed bugs are active during different times of day/night cycles

We will use a Raspberry Pi 3 board, which has built-in WiFi, 1.2 GHz quad core ARMv8 processor and 1 GB of RAM.

• This board comes with a built-in WiFi, 1.2 GHz quad core ARMv8 processor and 1 GB of RAM. It’s powered by a 5V micro USB that can be connected to any power source (wall adapter or computer)
• The board is small in size but powerful enough to accommodate your needs. It is also compatible with all Raspberry Pi accessories like the camera module etcetera.
• The price of this board varies depending on where you buy it from and what type of package deal you choose to go for but it shouldn’t cost more than 40 dollars for most models

We will use this board as it can allow for easy connectivity, given that we are using thermal imaging.

The Raspberry Pi 3 is an excellent choice for this project, as it has the following features:

• It is easy to use and can be programmed using Python.
• It has WiFi connectivity, making it possible to connect with our thermal imaging camera over the internet.
• It has Bluetooth connectivity that allows us to connect with other devices such as a tablet or smartphone.

We will use an Adafruit AMG8833 thermal camera sensor connected to the Raspberry Pi 3 board via I2C protocol.

The thermal camera sensor we will use is the Adafruit AMG8833. It is a high precision, low cost thermal camera from Adafruit with an accuracy of +- 2.5 degrees C on the temperature range from 0 to 80 degrees C and a maximum frame rate of 10 Hz. The device communicates via I2C protocol with the Raspberry Pi 3 board so we don’t need any extra libraries or software for that part of our project.

This project would be useful for houses, hotels, and any other places where bed bugs are common.

Bed bugs are a problem in every type of housing. It is important to detect bed bugs early so they can be eradicated before they become a larger problem that can spread to other rooms and even other properties. Bed bugs are not just a nuisance—they can cause allergic reactions, and they don’t have to be associated with poor hygiene. In fact, bed bug infestations have been found at hotels ranging from two-star motels to luxury resorts!

Bed bug detection is one of the most difficult parts of bed bug management because it requires extensive knowledge of how these insects behave under different conditions, including behavior during molting (shedding their skin), mating, feeding patterns and movement between hiding places such as cracks or crevices in walls/furniture where they often hide during daylight hours when people are awake and active around buildings.

Our final product is a device that uses thermal imaging to detect bed bugs in mattresses and alert you when they’re present.

Our final product is a device that uses thermal imaging to detect bed bugs in mattresses and alert you when they’re present.

Our device is self-contained, so there’s no need for an external computer or power source beyond the Raspberry Pi 3 board itself. The thermocouple sensor can be inserted into a mattress or other soft items to measure temperature, which is used as part of an algorithm trained by us (and eventually anyone) using data from our prototype hardware. The neural network classifies whether these temperatures are due to the presence or absence of bed bugs based on images taken by our thermal camera module (which can also be used independently with any other Raspberry Pi project).