## 3 Re-Usable Re-Constructible Sensor Device
### Software
#### 3.3.1 Intelligent Calibration
Furthermore, the same kit can be reorganized for different applications, further expanding the scope of the circular economy. For example, the embedded electronic component used in the case study here can be repackaged in another cardboard flat-pack for tracking the user's feet only, and it also has an expected set of actions for single users. #### 5.2.3 Making the Device Adaptable

Devices designed in this manner can be put anywhere by anyone. There is a possibility of misusing the device or at least deceiving it regarding its actual purpose. This aims to enable human users to make the device \"think\" that the actions are being taken correctly, as expected by the device's developer and the corresponding applications. This can be achieved by closely studying device operations. As the devices are low-cost and thus not designed with redundancies for monitoring, a hacker can find a way around their operation. For example, in the device for the case study, we assume that the human would stand and sit down. The values associated with the sensors are configured for an expected distance of approximately 90 cm. However, the differential distance can be achieved by simply putting the hand in front of the sensors and blocking it. The current software is designed to prevent such cheating by checking distance, but there may be additional ways to cheat on the device. AI can be used to process data for specific actions that have a distinct pattern. Some practical ways to use AI could be as follows:

* To analyze certain time periods for specific posture and counting. For example, if the user is asked to do 10 desk squats, that data would be collected in a few minutes, and the data analysis could focus on that small time period only to achieve higher accuracy. * For posture and movement classification, the user data can be labeled with the user identification details and used for training. The data needs to be labeled to identify specific actions taken by a user, and particular models can be created for those actions that can be used for multiple users. Data can be collected during calibration in short bursts of time for the same action. For example, the software could ask the user to stand up 10 times and record the time series for training. For this, the training data must be normalized to account for different user characteristics, such as height. #### 5.2.4 Seamless Integration and Friendly Operation

This device is designed for seamless integration into workspaces, including busy open plans and hybrid settings, with the aim of minimizing disruptions to users' workdays. The core concept of \"friendliness\" extends beyond ease of installation and maintenance; it emphasizes broad usability and reduces technical complexity. To achieve this, the device requires only a simple USB connection, eliminating the need for complex setup procedures. Unlike many IoT devices that rely on dedicated software or drivers, it operates without additional software installation by using the Web Serial API. This approach minimizes IT maintenance efforts, as data can be collected directly through a standard web browser. If the device functions within existing web environments, it seamlessly integrates with corporate security frameworks and protocols. This eliminates the need for extensive configuration orinfrastructure modifications, making it an ideal solution for dynamic workplace settings where ease of use and security compliance are equally important. Furthermore, the device's intuitive nature ensures that even non-technical users can set it up and operate it without specialized training. This enhances accessibility, allowing organizations to deploy the device widely without overburdening their IT support teams. #### 5.2.5 Data Collection and Cloud Computing

The device is designed with privacy in mind, ensuring that all collected data remains identifiable yet secure when processed in the cloud. By prioritizing privacy, we implement safeguards that protect user information while still enabling seamless data aggregation for analysis and insight.