Imagine…
After doing a chore on a hot summer day, you just walked into your home.
You are dead tired and slump into a chair near a window.
Immediately, the window blinds roll down to shade you from the blazing Sun coming through the window,
room lights adjust to create evenly diffused lighting,
the air-conditioner starts blowing cool air,
your music system starts playing soothing tunes that you like, and
fresh jasmine fragrance arises in the air to calm you down.
All these actions without you even uttering a word to your domestic help or to your Alexa.
Wouldn’t this be lovely… what seemed like a pipedream just a few years ago is now becoming a reality thanks to the seamless integration of various technologies already available to us.
Such intelligent systems are called ambient intelligence.
Overview
Ambient intelligence (AmI) refers to a system that understands an individual person’s needs, preferences, actions, and emotions, and responds accordingly to create the most-suitable personalized ambience without the need for direct interventions by the individual. Such systems can work in our living rooms, kitchens, workplaces, retail stores, cars, hotels, and even in hospitals.
Source: Research and Data
The Global AmI Market was valued at US$ 1.27 billion in 2022 and is expected to grow rapidly at CAGR of 13.2%, according to Reports and Data.
Despite expected overall growth, the AmI market is expected to grow unevenly in different countries. Largely, the growth will be fueled by the demand for remote monitoring and automation in healthcare, manufacturing, and logistics, coupled with the expanding adoption of smart homes/buildings, and the increase in investments in smart city infrastructure by governments and businesses.
Image Source: Mordor Intelligence
Key Characteristics
To enable ambient intelligence, the system needs to:
have simple and intuitive operations that reacts to gestures and language rather than traditional input devices like keyboard and mouse,
have analytical skills that enable target-oriented, flexible actions that are personalized to individual users,
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learn from the changing patterns of usage, and
incorporate inconspicuous components embedded in the environment around the user.
Various types of sensors and controllers are seamlessly integrated with an artificial intelligence enabled, self-learning pervasive computing network , which continuously collects vast amount of data and uses past patterns to infer preferences of the target individual and learns from and adjusts itself as the patterns change over time.
User Friendly
Ambient intelligence will be used by individuals, who may not be as conversant with technologies as engineers are. So, the systems used for ambient intelligence should be user friendly.
Personalized
Every individual is different, so ambient intelligent systems ought to be personalized to the needs, preferences, and personalities of the target individual.
Adaptive
People change over time, so do their needs and preferences. In addition, the ambience in which ambient intelligent systems are embedded also changes over time. So, AmI systems should automatically adapt to these changes.
Embedded
The sensors, cameras, microphones, and other technologies used to enable ambient intelligence should be integrated into the environment where the target individual is functioning.
Intelligent
AmI systems should be intelligent enough to anticipate a person’s needs and desires as well as the context in which the person is operating without any intermediation by the person.
Unobtrusive
An ambient intelligent system and all its components should be integrated into the surrounding structures, in a way that they are inconspicuous and blend into the background.
Enabling Technologies
Image Source: Infosys
Internet of Things (IoT)
Various types of sensors, such as RFID, face recognition, light, temperature, noise, pressure, humidity, etc. that collect real-time data, as well as actuators and controllers, such as relay switches, valves, motors, pneumatic mechanisms, etc. that activate and regulate relevant devices.
NFC/Bluetooth Wireless Communications
Enable real-time connectivity among IoT devices and pervasive computing and data processing units.
Pervasive Computing and Data Processing
Integrated edge, fog and cloud computing to manage data volumes, reduce latency and optimize processing.
Affective Computing
Systems and devices that can sense, interpret, and respond to human emotions.
Artificial Intelligence/Machine Learning Algorithms
Provides intelligent decision-making and adaptability by recognizing and inferring from the patterns of user behavior and reactions.
Human-Computer Interface
Enable interactions between individuals and AMI systems.
Who Would be Interested?
Smart Homes
Provide pleasant living experience to residents and guests.
Monitor the safety and security of occupants and pets.
Promptly and independently act in medical and other emergency situations.
Optimize energy consumption based on occupancy and weather conditions.
Healthcare
Facilitate telemedicine services.
Remote patient observations and monitoring vital signs.
Deliver precision medicine in a timely manner.
Retail
Enhance the entire shopping experience using smart mirrors, robotic assistance, and queue-less automatic billing and checkout.
Provide individualized recommendations to shoppers.
Optimize real-time inventory management.
Smart City Management
Mange urban infrastructure and community services.
Immediately adapt to the changing patterns of energy use, traffic movements, etc.
Enhance waste management.
Increase safety and security of neighborhoods.
Education
Monitor student behavior and performance.
Improve learning at the individual, group and institutional levels.
Automotive
Enable driverless cars with voice-controlled and advanced navigation systems.
Improve automotive safety, convenience, and comfort.
Optimize vehicle performance, fuel efficiency and entertainment systems.
Manufacturing Facilities and Workplaces
Improve working conditions in factories and workplaces.
Increase worker safety and reduce accidents with integrated voice-activated controls.
Optimize power production and distribution.
Key Considerations
Data Privacy
Continuous data collection and long-term data storage raise privacy concerns. New paradigms will have to be developed to mediate a person’s interaction with the world around them. In addition, issues of consensual monitoring and informed acceptance will have to be resolved.
At every point of data collection, the consent framework of the AmI-enabled appliances needs to be assessed and made in compliance with data protection laws of relevant jurisdictions. User consents would have to be based on a purpose, so personal data can be shared with connected devices, which could be belonging to even third parties, to improve experiences of the users.
In addition, protocol needs to be developed for sharing data with law enforcement authorities, especially when crime is suspected. This is relevant in consideration of inadvertent confessions related to criminal proceedings or court matters.
Data Security and Authentication
AmI depends on vast amount of personal and nonpersonal data stored at various locations--cloud, edge, device, etc.. This requires robust security measures to minimize all kinds of harms and calls for assessing the effectiveness of existing cybersecurity standards.
In the event of a cybersecurity breach in an ambient system, interoperability may attribute liability to multiple AmI companies which begs the question as to who would be responsible for breach incidents.
Authentication of who has access to which data is also an important consideration. Anonymizing personal data can reduce risks related to misuse of data through an unauthorized access. In addition, AmI technologies can use tokenization of data for authentication and traceability.
Commercialization of Data
A unique challenge is regarding ownership of datasets collected / generated by AmI technologies and rights of the involved parties to extract commercial value.
Since datasets are collected / generated from multiple connected devices, the ownership rights with each company could always be questionable. While every AmI company would be securing the right to collect data in their user agreements, ownership of cross-shared data sets which drives these environments could be questionable.
Developers and regulators would have to consider the potential consequences of data-sharing for purposes outside the original scope or source of the data and monetization of the data.
Interoperability
Ensuring seamless communication among diverse devices and platforms enabling ambient intelligence is a key technical challenge. It requires common communication protocols, electronic stacks, data formats, security standards etc.
AmI systems rely heavily on data gathered from the movements of the targeted individual, the surrounding environment, and historical behavioral patterns. Integrity of data and elimination of blind spots in the coverage area are essential for effective functioning of AmI.
While there are some industry-specific, voluntary consensus standards and guidelines, there are no enforceable international regulations in place to prevent platform/vendor lock-in and a closed ecosystem.
Failure to achieve cohesion among different parameters would lead to inefficiencies and poor user experience. Having international standards on interoperability could also ensure user privacy is retained at all instances.
Consumer Protection
Consumer Protection and product liabilities are other important issues. AmI systems use various types of sensors and control systems. It is very likely that some may malfunction in some conditions or due to the lack of preventive maintenance. Protecting user from harm caused by malfunctioning or hacking of these devices becomes paramount to ensure the trust in AmI systems.
Given the interoperability of devices in AmI, a malfunctioning of a device may have been caused by a command from another device. Principles of allocating responsibility need to be defined and reporting obligations to service providers need to be embedded in service contracts.
Intellectual Property
AmI systems use many types of technologies which may be protected by Intellectual Property rights of other parties. Developing overlapping AmI technologies or inadvertently deploying proprietary AmI technologies may lead to patent disputes and legal complexities.
Taxation
When a non-resident provides services in India through AmI technologies, tax questions may arise as to whether it would constitute a Permanent Establishment for the non-resident in India.
Ethical Concerns
Ethical considerations arise from the people being monitored, data collected without their knowledge or consent, autonomous decisions made by AmI systems, especially in critical scenarios. Bias and discrimination by AmI are other significant concerns.
Sources and Further Reading
Prepared By
With contributions by:
Abhay Porwal, Head, IPpro
Muqeet Drabu, Associate, Corporate
Huzefa Tavawalla, Leader, Technology
Nishith Desai Associates
For any questions on legal, regulatory, IP and tax issues related to disruptive technologies, reach out to:
Vaibhav Parikh, Leader, TMT and PE/VC Practices; Head, US Operations
vaibhav.parikh@nishithdesai.com
Dr. Milind Antani, Leader, Pharma/Lifesciences and NanoTech Practices
milind.antani@nishithdesai.com
Abhay Porwal, Head, IPpro
abhay.porwal@ipproinc.com
About US
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