Real-time indoor monitoring of total volatile organic compounds (TVOC) is essential for controlling pollution sources and improving air quality. Conventional studies frequently employ single-point measurement to assess overall room conditions, overlooking the spatiotemporal distribution dynamics of contaminants. Indoor TVOC levels can be monitored using wireless sensor networks, which offers an effective solution for monitoring purposes. The study establishes a low-cost Zigbee wireless sensor network to monitor the TVOC concentrations in various indoor areas and make spatiotemporal predictions of TVOC concentrations by using ordinary kriging (OK) and RBF interpolation models. To verify the practicability of the network, this technique was demonstrated in a chemical lab for spatiotemporal monitoring. The results of cross-validation showed that in the key monitoring areas, the Pearson correlation coefficients for the two interpolation methods of the sensor data were more than 0.83 and the root mean square errors were generally less than 0.85 ppm. This study proposes an innovative technical solution with a self-developed low-cost sensor network, which can explore the TVOC generation and dissipation process and provide scientific predictions for TVOC exposure in specific locations.