# Multi-User Activity Recognition Using Plot Images Based on Ambiental Sensors
## 3 Dataset and Data Representation
### Density Map Graphic Representation Method  
The graphic representation method used in our study [13] involves the creation of a density map based on the sensor activation signals. In order to represent the map as close as possible to reality, a matrix was created that contains the sensors and the locations where they are installed. As can be seen in Figure 2, this matrix was created by superimposing it on the house map and determining the matrix point where each mounted sensor is displayed. \begin{table}
\begin{tabular}{p{56.9 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Activity Number** & **Description** & **Persons** & **Activity Type** \\ \hline \multirow{2}{*}{1} & Fill medication dispenser in the kitchen using items obtained from the cabinet. Return items to the cabinet when done & Person A & Individual \\ \hline \multirow{2}{*}{2} & Hang up clothes in the hallway closet. The clothes are laid out on the couch in the living room & Person B & Individual \\ \hline \multirow{2}{*}{3} & a. Move the couch and coffee table to the other side of the living room & Person A and B & Collaborative \\  & b. Request help from Person A & Person B & Individual \\ \hline \multirow{2}{*}{4} & Sit on the couch and read a magazine & Person A & Individual \\ \hline \multirow{2}{*}{5} & Water plants located around the apartment. Use the watering can located in the hallway closet. Return the watering can to the closet when finished. & Person A & Individual \\ \hline \multirow{2}{*}{6} & Sweep the kitchen floor using the broom and dust pan located in the kitchen closet. Return the tools to the closet when finished. & Person B & Individual \\ \hline \multirow{2}{*}{7} & Play a game of checkers for a maximum of five minutes & Person A and B & Collaborative \\ \hline \multirow{2}{*}{8} & Set out ingredients for dinner in the kitchen & Person A & Individual \\ \hline \multirow{2}{*}{9} & Set dining room table for dinner & Person B & Individual \\ \hline \multirow{2}{*}{10} & Read a magazine on the living room couch & Person A & Individual \\ \hline \multirow{6}{*}{11} & Simulate paying an electric bill. Retrieve a check, a pen, and an envelope from the cupboard underneath the television in the living room. Use the telephone book in the dining room to look up a number for a utility company to confirm the amount on the bill. a. Person B requests help from Person A to find the number for the utility company & Person A and B & Collaborative \\ \cline{1-1}  & b. Person A will stop the current task to help and finish a task when done helping & & \\ \hline \multirow{2}{*}{12} & Gather food for a picnic from the kitchen cupboard and pack them in a picnic basket & Person A & Individual \\ \hline \multirow{6}{*}{13} & Retrieve dishes from a kitchen cabinet. & & \\ \cline{1-1}  & a. Person B requests help from Person A to identify the cabinet in which the dishes are located. & Person A and B & Collaborative \\ \cline{1-1}  & b. Person A will stop the current task to help and finish a task when done helping & & \\ \hline \multirow{2}{*}{14} & Pack supplies in the picnic basket & Person B & Individual \\ \cline{1-1}  & Pack food in the picnic basket and bring the basket to the front door of the apartment. & Person A & Individual \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Detailed activities scenario [32]. The more active a sensor is, the more intensely it is represented on the map, where it is highlighted by a different shade. Using this method, we generated images of \(227\times 227\) pixels using data from the Kyoto Multiresident ADL Activities set. In Algorithm 1, the pseudocode used to generate images using the density map method is presented. The first step is to read the input dataset file and initialize the activity group. For each line item in the dataset file, we check if we have a condition called activity begin. If an activity is starting, we add the current data item to the activity group.