# Integration of AI in Self-Powered IoT Sensor Systems
## 6 Self-Powered IoT Sensors in the AI Field
### Detailed Literature Analysis of Self-Power IoT Sensors in the AI Field
\begin{table}
\begin{tabular}{c c c} \hline
**Domain** & **Description** & **Reference** \\ \hline \multirow{8}{*}{Healthcare IoT} & Microneedle patches for biosensing & [201] \\  & Self-powered plantar stress sensing inside & [202] \\  & Bimode temperature-pressure self-powered sensor & [203] \\  & Self-powered leg system with AI & [204] \\  & Ultrasensitive self-powered mechanoluminescence smart skin & [205] \\  & Piezoelectric polymer nanofibers for pressure sensors & [206] \\  & Smart textile TENGs & [207] \\  & Performance of flexible TENGs & [208] \\ \hline \multirow{8}{*}{Industrial IoT} & Self-powered sensing in robotics and AI & [209] \\  & Smart bearing with self-diagnosis & [210] \\  & Hybrid vibration energy harvester & [211] \\  & Review of ML-assisted TENG sensors & [212] \\  & Self-powered sensing and intelligent systems & [213] \\  & On-device predictive maintenance system & [214] \\  & 3D printed conductive hydrogel-based energy harvesting device & [215] \\  & Advanced 3D printing-based TENG for mechanical energy harvesting and & [216] \\  & self-powered sensing & \\ \hline \multirow{8}{*}{Smart Cities} & Self-powered sensors in civil infrastructure & [217] \\  & Wind energy harvesting with AI & [197] \\  & ML for TENG-based sensing systems & [178] \\  & Intelligent piezoelectric AIoT node & [218] \\  & Self-powered sensing in rail transit & [219] \\  & Origami-inspired generator for IoT & [220] \\ \hline \multirow{8}{*}{Smart Homes} & Wood-based triboelectric sensor for smart homes & [221] \\  & Cellulosic TENG for sustainable sensing & [222] \\  & Self-powered speech recognition system & [223] \\  & Film and textile-based single electrode TENGS & [224] \\ \hline \multirow{2}{*}{Smart Mobility} & Hybrid backpack energy converter with AI & [225] \\  & Self-powered gyroscope sensor based on TENG & [226] \\ \hline \multirow{8}{*}{Smart Homes} & Dual-modal self-powered sensor for writing & [188] \\  & Thermoelectric fabric for respiration monitoring & [227] \\  & TENG applications in biomedical and AI & [228] \\  & Self-powered tactile sensing review & [229] \\  & CL@rGO hydrogel for self-powered sensing & [230] \\  & Multilayer hydrogel for self-powered sensing & [231] \\  & Multi-functional T-TENG with UV protection & [232] \\  & Organic thermoelectrics for sensing & [233] \\  & Triboelectric paper for tactile sensing & [234] \\  & Facial recognition mask using TENG & [235] \\  & Stretchable CCF fiber for sensing & [236] \\  & Graphene textile TENG for motion monitoring & [237] \\  & Intelligent E-skin with multimodal perception & [238] \\  & High-performance flexible piezoelectric sensor array & [239] \\  & Core-sheath piezoelectric sensor based on steel wire and PVDF microfibrillar bundle & [240] \\  & Fiber/fabric-based piezoelectric nanogenerators and TENGs & [241] \\  & Flexible electronic skins based on the composite of ALTFM & [242] \\  & Improved ultrathin stretchable TENG with postcharging material & [243] \\  & Water repellent fabric-based TENG for harvesting human mechanical energies & [244] \\ \hline \end{tabular} Note: ALTFM—Aligned liquid metal/thermoplastic polyurethane fibrous mat; DNN—Deep neural network; EMG—Electromagnetic Generator; GRU—Gated Recurrent Unit; RB-Tenc—Rolling Ball Triboelectric Nanogenerator; PVDF—Polyvinylidene fluoride; RF—Random Forest.  
\end{table} 
Table 4: _Cont._The analysis of these works shows that the combination of self-power sensing concerning AI primarily activates in smart cities, wearable devices, healthcare IoT, and industrial IoT through autonomous sensors that process and interpret data intelligently [178; 245]. The most commonly used sensors are TENGs, which collect ambient mechanical energy and convert it into electrical energy. This is why many studies investigate TENG technology combined with AI algorithms, such as LSTM, RF, DL, or Recurrent Neural Network (RNN) [204; 214; 235]. For example, the paper by [PERSON] et al. [235] is dedicated to an innovative mask for facial recognition using an LSTM model.