## 2 On-Device Object Detection for Context Awareness in Ambient Intelligence Systems
Furthermore, as far as domain-specific studies are concerned, it is possible to categorize them into five groups, intelligent transportation [68; 69; 77; 78; 79; 82; 85; 92; 96; 102; 105; 106], surveillance [67; 70; 75; 89; 90; 95; 98; 104; 109], smart farming [76; 80; 87; 91; 93; 107], healthcare [73; 74; 88; 97; 110] and smart cities [72; 100; 101; 108], all of them, scenarios where constant and real-time object detection is necessary for enabling context-awareness on end devices. While further information on each of those domains will be incorporated into the discussion in successive paragraphs to draw a clearer picture, it should be noted first that additional application areas, albeit almost residually with only one or two related works identified, have emerged in the analysis: (i) robotics [81; 94], a domain where vision represents one of the most important communication channels with the environment, and where object detection has traditionally shown to be critical for the perception, modeling, planning, and understanding of unknown terrains [94]; (ii) defense, where object detection constitutes a major factor for controlling UAVs [84] and detecting ships in radar images [86]; (iii) smart logistics, with two distinct but equally representative examples of the use of sensing technologies, one on embedded platforms (in situ detection and recognition of ships for more \begin{table}
\begin{tabular}{l l l l l l l} \hline \hline
**Work** & **Year** & **Application** & **Domain** &
\begin{tabular}{l} **Vision Task It** \\ **Supports** \\ \end{tabular} & \multicolumn{2}{l}{**High-Level Requirements**} \\ \hline
[98] & 2020 & Drone detection & Surveillance & – & & & \(\bullet\) \\
[99] & 2020 & Barcode detection & Smart logistics & \(\bullet\) \\  & & & & scanning & \(\bullet\) \\
[100] & 2020 & Waste detection & Smart cities & – & & \(\bullet\) \\
[101] & 2020 & Bus passenger & & \(\bullet\) \\  & detection & Smart cities & & counting & \(\bullet\) \\
[65] & 2020 & Vehicle and & & & & \(\bullet\) \\  & pedestrian detection & Generic & – & & \(\bullet\) \\
[102] & 2020 & Vehicle detection & Intelligent & & \(\bullet\) \\  & transportation & – & & \(\bullet\) \\
[103] & 2020 & Fruit detection & Smart farming & \(\bullet\) \\  & & & estimation & \(\bullet\) \\
[104] & 2020 &
\begin{tabular}{l} Human action \\ detection from \\ autonomous drones \\ \end{tabular} & Surveillance & – & – & – \\
[105] & 2020 & Vehicle and & Intelligent & – & \(\bullet\) \\  & pedestrian detection & transportation & – & \(\bullet\) \\
[106] & 2020 & Traffic sign & Intelligent & – & \(\bullet\) \\  & recognition & transportation & – & \(\bullet\) \\
[107] & 2020 & Plant disease & Smart farming & – & \(\bullet\) \\
[108] & 2020 & \
\begin{tabular}{l} Caribbean and \\ pedestrian detection \\ \end{tabular} &
\begin{tabular}{l} Intelligent \\ transportation \\ \end{tabular} & – & \(\bullet\) \\  & & & & \(\bullet\) \\
[106] & 2020 & Traffic sign & Intelligent & – & \(\bullet\) \\  & recognition & transportation & – & \(\bullet\) \\
[107] & 2020 & Plant disease & Smart farming & – & \(\bullet\) \\  & detection & Smart cities & – & \(\bullet\) \\
[108] & 2020 &
\begin{tabular}{l} Garbage truck \\ supervision \\ \end{tabular} & Smart cities & – & \(\bullet\) \\
[66] & 2020 & Calibration of object & Generic & \(\bullet\) \\  & tracking systems & & & \\
[109] & 2020 & Face mask & Surveillance & – & \(\bullet\) \\
[110] & 2021 & Navigation in open & Healthcare & \(\bullet\) \\  & surgeries & Healthcare & \(\bullet\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: \(Cont.\)efficient port management) [83], and the second one on mobile devices (barcode detection) [99] and finally, (iv) human emotion recognition based on facial expression detection, as reported in [71]. Once the less representative options are covered, the remainder of this section will deal with the most common domains that have emerged in the analysis.