# Integrating Machine Learning Techniques for Enhanced Safety and Crime Analysis in Maryland
## 3 Methodology
### Data Analysis
#### 3.4.4 Crime Trends According to the Victim's Age Group Across Crime Types  
The analysis of crime victimization trends across age groups, as illustrated in Figure 5, reveals notable patterns that provide insights into the dynamics of various crimes. Individuals aged 30-40 and 40-50 experience the highest levels of victimization for many crime types, including aggravated assault, larceny, and auto theft. These findings suggest that individuals in their prime working years are particularly vulnerable to these types of crimes, due to their active lifestyles, frequent interactions with public spaces, and higher rates of economic activity. Violent crimes such as aggravated assault, shooting, and homicide disproportionately affect younger adults aged 20-40. Aggravated assault (Figure 5b) demonstrates a sharp concentration of victims in this age group, tapering off among older populations. This pattern reflects the increased exposure of younger individuals to high-risk environments and conflict-prone situations, such as urban centers or workplaces with elevated stress levels [53]. Similarly, shootings (Figure 5f) and homicides (Figure 5e) follow this trend, with victimization peaking for individuals in their thirties. These crimes are often linked to systemic issues like poverty, social inequality, and gang-related activities, which disproportionately impact younger populations [60; 61]. Rape (Figure 5h) exhibits a distinct pattern,  
Figure 5: Crime trends, grouped according to the victim’s age group across crime types: (**a**) laxeny, (**b**) aggravated assault (**c**) auto theft, (**d**) arson, (**e**) burglary, (**f**) homicide, (**g**) shooting, (**h**) robbery, and (**i**) rape. with victimization heavily concentrated among individuals aged 20-40. The sharp decline in cases for those aged 60 and above reflects reduced exposure to social environments where such crimes are more likely to occur and age-related lifestyle changes [57]. Property crimes like larceny, auto theft, and burglary show broader age distributions but exhibit distinct trends. Larceny (Figure 5a) emerges as one of the most widespread crimes, affecting individuals across all age groups. Victimization peaks in the 30-40 age range but remains significant among older adults aged 60-70, likely due to the targeting of elderly individuals for theft or fraud [55]. Auto theft (Figure 5i) similarly peaks for those aged 30-50, reflecting higher rates of vehicle ownership and usage in these groups. The decline in auto theft victimization after age 60 may correspond to reduced vehicle ownership among older adults [57]. Burglary (Figure 5d) disproportionately impacts individuals aged 30-60, with notable victimization seen in the 50-70 age range. This trend suggests that the homes of older individuals may be targeted due to perceived vulnerabilities, such as lower levels of home security or physical limitations. Arson (Figure 5c), while a less frequent crime overall, shows a relatively even distribution of victims across age groups. Individuals aged 30-40 and 40-50 experience slightly higher rates, which is consistent with the general trend of these age groups being more affected by various crimes. This even distribution reflects the sporadic nature of arson incidents and their dependence on factors unrelated to specific age groups. The data collectively suggest that victimization risks vary significantly across age groups, with younger adults (20-40) being disproportionately affected by violent crimes such as aggravated assault, rape, shooting, and homicide. Conversely, older adults (60 and above) face a higher risk of property-related crimes, including larceny and burglary. These trends highlight the need for age-specific crime prevention strategies. For younger populations, prevention efforts should focus on reducing their exposure to environments that foster violent crime, such as urban areas with high crime rates or conflict-prone settings.