## 3 Results
Some employ basic validation methods, while others conduct more comprehensive analyses. For instance, S30 specifies that its prototype operates with an acceptable error margin of less than 5% when dispensing food portions of 200 g or more, making it suitable for medium and large pets. In scheduled mode, the water supply and replacement were successfully executed in 100% of the conducted trials. Similarly, in S59, researchers achieved a 98% accuracy in measuring food portions supplied to the pets. Study S12 reported an accuracy of 99.3%, while S5 achieved an 88.38% accuracy in food weight measurement. Regarding aquatic pets, S58 attained a 92% accuracy in its fish feeding system, though the researchers attributed the remaining error to the small size of the fish food granules, which affected the number of pellets dispensed into the tank. Additionally, S72 employed fuzzy logic to regulate the ideal portion size for a cat, achieving a 100% precision in the operation of a servo motor used to control the food dispensing outlet. Further research on nutritional control in pets includes S61, which was specifically evaluated with dogs. This study employed feeding data to implement precise nutritional control. The experimental results assessed the amount of leftover food compared to the supplied portions over different hours of the day. The findings revealed distinct feeding patterns based on the dog's age. Puppies tend to overeat, necessitating portion adjustments. Young adult dogs maintain a balanced diet. Senior dogs often consume less than required, indicating the need for age-appropriate dietary supplements. Finally, S49 conducted the most rigorous tests to evaluate the effectiveness of its pet feeding prototype, particularly concerning portion accuracy. The device demonstrated a precision rate of 96.94% when dispensing pre-determined food portions for pets. Additionally, the prototypes analyzed also focused on aspects beyond providing food. The majority were oriented towards tracking pets for health monitoring (e.g., S6, S7, S23, and S35), emotional support (e.g., S18, S19, S25, S26, S33, S48, and S56), providing thermal comfort (e.g., S14, S32, S40, S41, and S59), cleaning of defecation areas (e.g., S12, S16, and S20), or simply for location and/or activity tracking (e.g., S4, S6, S7, S17, S23, S34, S35, S39, S62, and S65). Some prototypes were also designed for remote pet monitoring, particularly during owner absences or veterinary stays (e.g., S23 and S25). Furthermore, they addressed the management of spaces where pets relieve themselves, such as litter boxes. These kinds of prototypes are illustrated in Figure 6.  
Figure 5: Prototypes based on the Internet of Pets for food dispensers. More specifically, Table 2 shows the main functions of IoT device prototypes designed for pet care. The analysis of the 81 reviewed studies reveals a significant trend towards the development of prototypes for general pet care, dogs, cats, fishes, turtles, chickens, and rodents such as hamsters, rats, or hedgehogs. For these types of pets, which typically cohabit in households, various devices have been proposed, including food and/or water dispensers (e.g., S2, S3, S5, S8, S9, S10, S12, S13, S16, S20, S21, S27, S28, S29, S30, S31, S36, S40, S50  
S37, S38, S44, S45, S47, S48, S49, S50, S51, S52, S54, S55, S57, S60, S61, S63, S64, S65, S66, S67, S68, S70, S71, S72, S74, S75, S76, S77, S78, and S80), cages (e.g., S25, S34, and S40), small pet houses (e.g., S14, S22, S41, S59, and S62), daily care robots (e.g., S4, S24, S42, S43, S69, and S73), tanks or aquariums (e.g., S1, S26, S53, and S58), collars (e.g., S6, S7, S21, S33, S34, and S66), other wearable devices (e.g., S19 and S35), exercise boxes (e.g., S11), door and/or access mechanisms (e.g., S15, S16, S21, S39, S46, and S56), defecation pads, IPTV systems (e.g., S18 and S20), cooling enclosures (e.g., S32), playmates (e.g., S56), and pet detection systems (e.g., S16, S20, and S81).