## 1 Introduction
[22] used deep learning methods for the identification of faults in pumps, and in 2019, [PERSON] et al. [23] used direct-write piezoelectric transducers to monitor ultrasonic wave signals and analyze structural health. This method detects defects in pipe structures. Moreover, piezoelectric sensors connected to an Arduino microcontroller board measured the energy available to be harvested from rainfall [24] in which a similar procedure could be replicated to detect the droplets of water in a leaky and running faucet. Water droplet measurements can also be used to minimize needless water waste in appliances like toilet tanks [12]. Emerging Augmented Reality (AR) technology has proven to assist maintenance professionals in performing their duties. AR assistance can lead to greater efficiency when compared to operators without AR, particularly with preventative maintenance and repair [25]. Additionally, AR systems can offer remote guidance to amateur personnel for routine maintenance tasks [26], reducing training time and providing superior effectiveness when compared to Virtual Reality (VR) in multi-level and complex maintenance tasks [27]. A variety of interfaces have been developed for AR, such as those used in equipment maintenance and diagnostics [28], intuitive teleportation of bimanual robots [29], and steering the MARShot microrobot for the inspection of tight spaces and Unistrut channels [30]. AR platforms offer a variety of applications such as interacting with RFID [31] and the inspection of hard-to-reach areas using robots for Structural Health Monitoring (SHM) industries [32]. Despite efforts to advance the state of the art in cyber-physical systems, comprehensive research on incorporating such systems into human-building interaction is limited. The complexity of these technologies may be the reason for lack of Do-It-Yourself (DIY) use in homes as they are designed for maintenance professionals, rather than homeowners. Nonetheless, sensing technologies are becoming low-cost and IoT devices are becoming widely available in homes. This paper addresses the common maintenance problems that typical homeowners may encounter, such as pump failure, pest infestation, foundation damage, water leakage, and mold contamination, depicted in Figure 1, and employs cyber-physical approaches using ML and AR to provide user-friendly feedback to the homeowners. AR and VR headsets are becoming readily available for the typical household and have largely been used for entertainment purposes [33]. The proposed systems described herein demonstrate the potential for expanding these devices from pure entertainment to true multipurpose devices, opening new markets for manufacturers and developers as well as opportunities for consumers. Considering that the interfaces in these devices are becoming more user-friendly, combining these systems with the described sensor applications will create novel home maintenance solutions. The main contributions of this paper are outlined as follows:  
1. An introduction of the Home Maintenance 4.0 framework for technical innovation to support home maintenance. 2. The integration of custom home maintenance sensors into a wireless network, with machine learning analysis of conditions, that interacts with humans and teams of humans through augmented reality interfaces. Figure 1: Demonstrated areas of human–building interaction where these proposed technologies are beneficial. 3. The utilization of a Quadruped Robot Dog (QRD) to inspect confined spaces for air quality and provide mobile LiDAR-based mapping and geometric configuration assessment of structures. 4. The novel integration of ESP32-CAM, battery, and HEXBUG devices that crawl into tight spaces, such as ceiling and wall voids, to provide wireless first-person views of conditions. 5. The provision of internet and database links to users for potential maintenance remedies and parts suppliers. 6. Assistance to homeowners in detecting and finding their missing tool objects for maintenance or objects obstructing narrow passages via the AR interfaces.