Smart home, more autonomous life: home automation at the service of people across the spectrum

Introduction: everyday autonomy, technological support and diversity within the spectrum

Everyday autonomy does not mean performing all activities without assistance, but rather having adjustable supports that allow individuals to decide on, initiate, complete, or review meaningful actions. Autistic individuals present highly diverse profiles in communication, sensory processing, executive functions, mobility, and support needs; therefore, the same technology can facilitate participation for one person while increasing the cognitive load for another. Difficulties in planning, organizing, and coping with change can interfere with daily living activities and social participation, especially when intellectual disability is also present (Kļaviņa et al., 2024) . Assistive technology is appropriate when it expands the individual’s control and is integrated into real-world contexts, not when it replaces their decisions.

Recent reviews describe the benefits of mobile apps, virtual reality, interactive software, and conventional devices for practical skills, communication, and social interaction, although they also point to problems with access, training, and personalization (Kļaviņa et al., 2024; Sousa et al., 2024) . Home automation adds an environmental dimension: it can adapt signals, record changes, and activate support without requiring the user to continually make a request. The goal, therefore, is not to automate domestic life in the abstract, but to build predictable and modifiable environments that respect the diversity of the spectrum. This distinction guides the review of assistive technologies, smart homes, sensory adaptation, and wearable devices.

Assistive technologies to develop practical skills and everyday participation

Routines, activities of daily living and self-regulation through visual supports

Assistive technologies facilitate learning activities by breaking down a task, presenting information in an understandable format, and allowing support to be adjusted based on observed performance. A systematic review of 18 studies concludes that these tools are associated with improvements in daily living skills, independence, communication, and social participation in individuals with autism or intellectual disabilities (Kļaviņa et al., 2024) . The outcome depends not only on the device but also on the compatibility of the interface, the task, sensory preferences, and the level of support required. General-purpose phones, tablets, and apps can be sufficient when they offer reminders, images, sequences, or step verification without requiring specialized equipment.

Visual supports make explicit a sequence that would otherwise have to be held in working memory. An Internet of Things-based routine system proposes that the family configure tasks, the individual receive visual cues and timed reminders, and the system record completion in real time (Krishnammal et al., 2026) . Its technical operation, with cloud synchronization and browser access, facilitates use at home or school, although the cited study primarily evaluated notification delivery and recording, not the longitudinal acquisition of autonomy. Feedback must be able to be withdrawn gradually; otherwise, the reminder can become a new dependency.

Self -regulation can also be supported by technologies that link physiological or behavioral signals to personalized interventions. A review of wearable devices distinguishes between signal acquisition systems and interactive feedback systems, designed to adapt stimuli and support to individual needs (Gao et al., 2024) . This formulation expands upon the visual routine, but the evidence does not allow us to assume that detecting physiological arousal alone identifies an emotion or need. Interpretation must remain open to the individual’s communication and the contextual knowledge of their support staff.

From continuous supervision to graduated autonomy and social inclusion

The criterion for success should shift from task completion to the control the individual retains over it. Assistance can be useful if it enables the user to initiate a purchase, navigate a space, prepare a meal, or communicate with less intervention from another person. A review of assistive technologies links these tools to greater independence and participation, but also cautions that their use must be self-regulated to contribute to inclusion (Kļaviņa et al., 2024) . Gradation requires selecting what information is displayed, when a hint is offered, and when human support is requested.

Social inclusion introduces demands that cannot be met with a functional interface alone. An international qualitative study identifies barriers related to communication, physical accessibility, stigma, lack of training, and insufficient participation of families and users in technological development (Sousa et al., 2024) . The device must enable participation in shared activities, not isolate the individual through procedures that only work in therapeutic contexts. It is also important to consider whether the technology is discreet, portable, and acceptable to the user, as the visibility of the assistive device can affect its use in social settings.

Professional experience confirms that structure, communication, and independence can be improved, but that available time, resources, and staff competence condition daily implementation (Ajla, 2025) . Graduated autonomy requires training to interpret errors, adjust levels of assistance, and prevent digital supervision from replacing meaningful contact. Thus, assistive technologies form a basis for home automation, provided that activity data becomes an opportunity for choice and not merely a compliance indicator.

Smart homes to anticipate, detect and respond to daily needs

Sensors, the Internet of Things, and artificial intelligence in activity tracking

A smart home integrates sensors, connected devices, and decision rules to monitor environmental conditions or daily activities. Reviews of older adults and people with disabilities describe systems that combine environmental sensors, wearable devices, voice assistants, the Internet of Things, artificial intelligence, and robotics to support independence, safety, and activity monitoring (Looti & Abd-Alazim, 2026) . In autism, this infrastructure can anticipate changes, detect risk situations, and provide an adapted signal, but automatic detection should not be confused with a complete understanding of behavior.

Multi-sensor systems illustrate how this chain is constructed. A prototype for rooms for autistic children combines motion, temperature, sound, and light using a microcontroller, classifies safety states with fuzzy logic, and sends visualizations and alerts through a digital platform (Taufiq et al., 2025) . Its value lies in combining signals that, separately, would be ambiguous. Even so, classifying a room as safe, requiring attention, or critical describes the state defined by the system, not necessarily the child’s subjective experience or the cause of the behavior.

Another approach represents daily activity data using ontologies, RDF, a triplet store, and SPARQL queries that generate rules to detect problems and visualize results on a clinical dashboard (Giannios et al., 2024) . Although this work focuses on individuals within the dementia spectrum rather than the autistic population, it illustrates a transferable architecture for transforming scattered records into interpretable information. This transfer cannot be taken for granted: routines, indicators of distress, and deviance criteria must be validated with autistic individuals and their support networks. Artificial intelligence can expand detection capabilities, but a review of tools for neurodevelopmental disorders underscores the need for human oversight, privacy protection, and longitudinal assessment (Shahini et al., 2025) .

Monitoring physiological signals offers an additional approach. One proposed system combines wearable devices, anomaly detection models, and machine learning with privacy protection to identify stress patterns in real time; its simulation results indicate greater accuracy and fewer false alarms compared to a reference, although this does not equate to clinical efficacy in real-world households (Hasan et al., 2024) . An appropriate response should incorporate contextual confirmation, pause options, and accessible communication, as an anomaly may reflect pain, noise, fatigue, a change in routine, or a sensor malfunction.

Remote assistance, security, and personal control in home environments

Remote assistance can reduce the need for continuous presence by offering on-demand instructions, communication, or intervention. Smart glasses have been studied for their support of young adults during an online shopping task; the study compared 22 autistic participants with 22 non-autistic participants and found average good usability in both groups, although the autistic group had more difficulty with ease of use (Osman & Lamash, 2025) . The analysis identified a subgroup of 19 participants with sensory, executive, and emotional characteristics more compatible with the device, demonstrating that suitability cannot be inferred from diagnosis alone.

In home security, automation can detect unusual movements, environmental conditions, or lack of response and notify a trusted person. This function is especially relevant when verbal communication is limited or when a self-care activity involves risk. However, a proposed automated portable toilet is still in the simulation and expert evaluation phase; its results indicate technical feasibility, but not safety or effectiveness for real users (Saigh, 2026) . The difference between prototype, simulation, and everyday use must be clearly defined when evaluating any system.

Personal control requires that the individual be able to activate, mute, or modify assistance and know who receives the data. Reviews of smart homes point to persistent problems of privacy, cost, usability, accessibility, and technical dependency (Looti & Abd-Alazim, 2026) . Studies with users with various disabilities also link adoption to convenience, safety, and independence, but describe barriers stemming from complexity and inconsistent operation (Moon et al., 2025) . Therefore, the smart home should be organized as a network of reversible supports: sensors to inform, algorithms to suggest, and people to decide, with the minimum intrusion compatible with safety.

Sensory adaptation and wearable technologies to adjust the environment to the person

Sensory rooms and real-time environmental monitoring

Sensory adaptation is based on the premise that the environment can contribute to discomfort or facilitate participation. Adaptive sensory rooms incorporate visual, auditory, tactile, deep pressure, olfactory, or vestibular stimuli, but a review of 13 studies found heterogeneous designs, equipment, and outcomes, as well as mixed evidence and safety or training protocols only in some of the studies (Williams et al., 2024) . The mere presence of equipment does not guarantee that a room will be beneficial for everyone. Its configuration should respond to individual preferences, functional goals, and observable signs of comfort or overload.

A sensory room design connected via the Internet of Things incorporates RFID identification, control panels, web interfaces, and relaxing, stimulating, personalized, and active modes (Reddy et al., 2025) . Functional evaluation recorded 88% satisfaction among 35 professionals, but this measure reflects the professionals’ assessment, not demonstrated changes in children’s autonomy, participation, or well-being. Technological personalization can facilitate rapid adjustments, but it can also increase the number of decisions made by non-autistic adults.

Environmental monitoring allows for intervention before sensory overload reaches a level that is difficult to manage. A web-based tool integrates acoustic measurement, detection of people and animals, analysis of chromatic salience, motion, and ambient light into a composite sensory stress index, with visual alerts for caregivers and educators (Trevisi, 2026) . Its field observations are preliminary, and its index should not be interpreted as a universal clinical measure. The system can describe environmental conditions, but the individual remains the primary source for determining whether those conditions are tolerable.

Wearable devices, personalized feedback, and assistance via smart glasses

Wearable devices can acquire physiological signals and provide feedback, allowing support to accompany the individual outside of an adapted room. A review of this technology identifies potential for real-time monitoring, personalized intervention, and support for sensory, psychological, behavioral, social, and cognitive difficulties (Gao et al., 2024) . However, its usefulness depends on the fit between sensors, comfort, privacy, and the meaning of the signal. A device that produces frequent alerts can increase vigilance and distract from the primary activity.

The integration of AI and the Internet of Things has been proposed to detect stress patterns and reduce false alarms using personalized models (Hasan et al., 2024) . These results come from simulations, so they do not yet establish that an alert improves self-regulation at home. Smart glasses add remote communication and guidance during tasks, but their ease of use was related to sensory, executive, and emotional characteristics, supporting individual selection rather than a general prescription (Osman & Lamash, 2025) . Sensory adaptation achieves its purpose when it increases a person’s scope of action, not when it turns every bodily response into monitored data.

Critical synthesis: personalization, co-design, and the boundaries between support, surveillance, and autonomy

The role of autistic people, families, and professionals in technological design

Personalization must begin before selecting sensors or applications. Autistic individuals need to be involved both as users and as experts on their own experience, while families and professionals contribute knowledge about routines, risks, support, and maintenance. A scoping study on co-design shows that caregivers appear to be poorly involved and, when they do participate, they often act as representatives of autistic individuals rather than expressing their own needs ( Waardenburg et al., 2025) . This dual perspective requires distinguishing the voice of each participant and preventing the family from overriding the individual’s decision-making.

International experts agree on the potential of assistive technologies for autonomy and inclusion, but describe differences between groups and settings conditioned by cultural, social, and economic factors (Tsvetkova et al., 2024) . The design should include iterative testing in real-life activities, training for caregivers, and mechanisms to modify or refuse assistance. Technology becomes meaningful when it aligns with valuable occupations and the individual’s life situation, not just when it meets technical specifications (Ajla, 2025) .

Usability, comfort, privacy, and variability of individual responses

Usability includes comprehension, effort, sensory comfort, reliability, control , and the ability to leave the system. Families show a preference for tablets due to their convenience and ease of use, while virtual reality and robots are less accepted because they are overwhelming, expensive, or impractical (Kouroupa et al., 2024) . User experiences with disabilities also link continued use with independence, peer feedback, and adaptation to the environment, but they maintain concerns about accessibility and reliability (Moon et al., 2025) . Privacy should be considered a condition of autonomy, because recording every movement can limit freedom even if it increases the amount of available information.

Gaps in the evidence and priorities for truly inclusive home automation

Scarcity of longitudinal and outcome assessments focused on independent living

Current evidence is concentrated in reviews, prototypes, simulations, usability studies, expert opinions, and performance tests. Longitudinal evaluations are lacking to determine whether assistive technologies maintain their usefulness, allow for the withdrawal of supervision, and improve person-defined outcomes, such as choosing activities, managing the household, or participating in the community. The AI review cautions that positive results in controlled environments do not guarantee clinical application and calls for long-term evaluation (Shahini et al., 2025) . Similarly, the smart home review identifies reported benefits but also uncertainty about actual outcomes and technical dependence (Looti & Abd-Alazim, 2026) .

Future research should compare support levels, record adverse effects, and measure functional autonomy along with well-being, comfort, and perceived control. It should also include autistic individuals of varying ages, communication abilities, support needs, and living conditions. Without this diversity, algorithmic precision may mask a lack of everyday relevance.

Need for interoperability, economic accessibility and adaptation to different life stages

Interoperability would allow reminders, sensors, wearables , and assistants to share information without forcing families to maintain incompatible systems. Affordability is equally crucial: cost, insufficient training, and a lack of awareness limit the adoption of assistive technologies (Sousa et al., 2024) . Designs should support simple configurations, local operation where possible, and repair and upgrades without requiring system replacement. Adaptability should also encompass childhood, adolescence, adulthood, and old age, as routines, responsibilities, and preferences evolve over time.

Conclusion: principles for putting home automation at the service of autonomy

Inclusive home automation must begin with a situated definition of autonomy: deciding, participating, and receiving the necessary assistance with the least amount of external control compatible with safety. Visual technologies, sensors, artificial intelligence, sensory rooms, and wearable devices offer complementary resources, but the evidence still shows more viability and acceptance than long-term effects on independent living. Therefore, every system must incorporate personalization , co-design , reversibility, affordability, and data protection from its inception.

Individuals with autism must be able to understand how technology works, modify it, reject it, and request human support. Families and professionals need training to interpret signals without resorting to automatic diagnoses or constant monitoring. Validation should take place in real homes and activities, with outcomes focused on choice, participation, comfort, and effectively reducing unnecessary support. A smart home fulfills its purpose when it adapts the environment to the individual and expands their opportunities for action, not when it transforms daily life into a sequence of monitored data.

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