The Inventive Edge - July 2025

THOUGHT LEADERSHIP

Overview of CRI Guidelines 2025 And Comparison with 2017 Guidelines

[Contributor: Gagandeep]

Introduction

The “Guidelines for Examination of Computer Related Inventions (CRIs), 2025”, issued by the Office of the Controller General of Patents, Designs, and Trade Marks, mark a progressive and jurisprudentially enriched framework for assessing the patentability of computer-related inventions in India. The 2025 guidelines aim to foster clarity, consistency, and efficiency in the examination of software, algorithm, and hardware-software integrated inventions while ensuring compliance with Section 3(k) of the Indian Patents Act, 1970.

Context and Objective

The guidelines recognize the transformational role of emerging technologies in shaping innovation. Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Quantum Computing, Blockchain, Edge and Cloud Computing, and Internet of Things (IoT) are acknowledged as cutting-edge fields that require nuanced examination. The CRI Guidelines 2025 aim to identify what qualifies as “technical contribution” or “technical effect” and how such inventions can qualify for patent protection even when based on software.

The core objective of these guidelines is to clarify the exclusions under Section 3(k), which prohibits patents for: Mathematical methods, Business methods, Algorithms and Computer programmes per se. However, the guidelines explicitly state that software inventions which demonstrate technical contribution or technical effect are not excluded from patentability.

Legal Framework and Jurisprudence

The guidelines are rooted in the Patents Act, 1970 and its definitions of invention, inventive step, industrial applicability, and the exclusions under Section 3(k). A notable development is the integration of Indian jurisprudence that interprets “technical effect” and “technical contribution” in favor of patent eligibility.

Key cases cited include:

• Ferid Allani v. Union of India - upheld that technical effect makes a software-based invention patentable.
• Microsoft Technology Licensing v. Controller of Patents - emphasized that technical solutions implemented on general-purpose computers may be patentable.
• Raytheon Company v. Controller of Patents - clarified that novel hardware is not a prerequisite for patentability of CRIs.
• Blackberry Ltd. v. Controller of Patents - distinguished between bare algorithms and their practical implementation in systems.

These judgments help the Examiners differentiate between excluded subject matter and legitimately patentable inventions.

Examination Procedure

The examination of CRI applications is conducted using standard criteria such as:

• Novelty, Inventive Step, Industrial Applicability and Sufficiency of Disclosure

However, special attention is given to determine whether the claimed subject matter falls within the excluded categories. To assist this, the guidelines introduce systematic approaches such as:

a. Seven Stambhas (Pillars) for Novelty Assessment:

• Understanding the claims
• Identifying prior art
• Analysing prior art in detail
• Evaluating explicit or implicit disclosures
• Identifying material differences
• Evaluating the novelty in combination
• Documenting novelty findings

b. Five-Step Inventive Step Assessment: The following points need to be objectively judged to ascertain whether, looking at the invention as a whole, the invention does have inventive step or not:

• Identify the person skilled in the art.
• Define the common general knowledge.
• Identify the inventive concept.
• Compare prior art with the claim.
• Determine if the invention would have been obvious.

The guidelines stress that inventive step should not be based on economic significance alone and must demonstrate technical advance not related to excluded subject matter.

Form and substance

The CRI Guidelines 2025 clarify that Section 3(k) does not restrict The Applicants to only method or only system claims. If the patent specification provides sufficient descriptive support, both method and system claims may be allowed even as independent claims. There is no bar on claiming both forms in the same application. To guide the Applicants and the Examiners, the Guidelines include a non-exhaustive list of allowable and non-allowable method/system claim examples in Annexure I, illustrating how technical effect and claim structure influence patentability.

Key Concepts and Definitions

The CRI Guidelines 2025 lay strong emphasis on understanding and correctly applying key concepts when examining patent applications related to computer-related inventions (CRIs). These definitions serve as the foundation for deciding whether a claimed invention falls within the scope of patentable subject matter, particularly in light of Section 3(k) of the Indian Patents Act.

• Algorithm refers to a finite set of step-by-step instructions designed to perform a task or solve a problem. By itself, an algorithm is considered an abstract concept and hence not patentable. However, if it is embedded within a technical process and leads to a technical effect such as improved processing, data management, or interaction with hardware then it may qualify for patent protection.
• Computer Programme per se signifies software claimed in isolation without any integration into hardware or absence of a functional technical contribution. Such claims are categorically excluded from patentability under Section 3(k). However, if the programme is applied to bring about a technical solution to a specific problem, it may be considered patentable.
• Technical Effect is a central term in CRI assessment. It encompasses improvements in system performance such as increased processing speed, efficient memory usage, enhanced user interface, robust security protocols, or reduction in network latency. The presence of a tangible, practical benefit through the implementation of a computer-related invention indicates a technical effect.
• Technical Contribution is closely related to technical effect. It refers to the advancement or input the claimed invention provides in solving a technical problem within a specific domain. This contribution must go beyond simple automation or data handling and must involve a meaningful improvement in a technical process or field.

The core test for patentability as per the 2025 guidelines is not merely whether an invention uses a computer, but whether the computer-related feature contributes to a technical result or solves a technical problem. This shift from focusing solely on software presence to evaluating technical outcome aligns Indian practice with international standards and court rulings. This nuanced interpretation allows genuine technological innovations especially in fields like AI, blockchain, and IoT to be considered for patent protection, while still respecting statutory exclusions.

Determination of Excluded Subject Matter Relating to CRIs

The determination of excluded subject matter in computer-related inventions is essential during patent examination. The CRI Guidelines 2025 provide clarity on assessing whether an invention involving software, algorithms, business methods, or mathematical models falls within the exclusions under Section 3(k) of the Patents Act. The focus is not merely on the claim format but on whether the invention contributes technically or solves a real-world technical problem.

Computer Programme per se

Computer programmes claimed in isolation without technical effect or hardware integration are excluded from patentability. However, if the programme demonstrates technical contribution, it may be allowed. Steps (Refer Fig. a below) for Assessing whether the claimed invention falls under the exclusion of computer programme per se or Not:

• Step 1: Construing the substance of claimed invention as a whole and identifying the essential technical features.
• Step 2: Identifying the core problem addressed by the invention and the solution it proposes and thereby determining the technicality.
• Step 3: Determining whether the identified technicality results in a technical effect- which is beyond a mere incidental effect.
• Step 4: If the determination in step 3 results into affirmation, then the claimed subject matter does NOT fall under the exclusion of “Computer Programme per se”; else the claimed subject matter is excluded under “Computer Programme per se” of section 3(k).

Algorithm

Algorithms, when claimed as logical or decision-making steps alone, are excluded. However, if embedded in a system and producing a technical outcome, they may be patentable.Steps (Refer Fig. b below) for assessing whether the claimed invention falls under the exclusion under “Algorithm” or not:

• Step 1: Construe the substance of claimed invention and thereby Identification of series of Steps.
• Step 2: Determination of Enablement/Abstractness: The identified series of steps in Step 1 shall be assessed to determine –

a) Whether the identified series of steps have a level of abstractness devoid of technical specifics or components needed to implement those steps,

OR

b) Whether the identified series of steps are enabled in the sense that they have the technical specifics/components needed to implement those steps, detailing the technical implementation and if this results in a technical solution to a real-world problem.

• Step 3: If the determination in step 2 matches with 2(a), then the claimed subject matter falls under exclusion of “Algorithm”; else if the determination matches with 2(b), then the claimed subject matter does NOT fall under exclusion of “Algorithm”.

Business Method

Business methods are not patentable if they simply automate administrative or commercial processes. Patentability arises only if the method is tied to a technical system that solves a real-world technical problem. Steps (Refer Fig. c below) for assessing whether the claimed invention falls under the exclusion under “Business method” or not:

• Step 1: Determine if the invention merely automates a business process.
• Step 2: Evaluate whether technical components (e.g., secure networks, devices) are involved.
• Step 3: Check if the implementation solves a technical problem, not just a commercial one.

Mathematical Method

Abstract mathematical formulae or models are excluded unless applied within a specific technical context to achieve a technical effect. Assessing whether the claimed invention is a mathematical method (Refer Fig. d above):

• Step 1: Construe the substance of claimed invention
• Step 2: Determination regarding the identified solution

a) Whether the solution, in its essence, lies in abstract mathematical processing by inherently showing only operations/functions of equations, statistical models, mathematical computations or alike, only to define any output.

OR

a) Whether the mathematical processing is not the primary objective but part of a larger technical process, where the output calculation is not the main aim rather it contributes to achieving a broader technical objective

• Step 3: If the determination in step 2 matches with 2(a), then the claimed subject matter falls under exclusion of “Mathematical Method”; else if the determination matches with 2(b), then the claimed subject matter does NOT fall under exclusion of “Mathematical Method”.

Examination of Inventions Related to AI, ML, DL, Blockchain, and Quantum Computing

The CRI Guidelines 2025 acknowledge the rapid growth of emerging technologies and provide domain-specific directions for examining inventions in areas such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Blockchain, and Quantum Computing. Chapter 5 of the guidelines offers a clear framework to evaluate such inventions on the basis of their technical contribution and real-world applicability.

• For AI/ML/DL-based inventions, mere use of algorithms, models, or neural networks is not sufficient. The invention must demonstrate how these are applied to solve a specific technical problem in a practical domain such as medical diagnostics, predictive maintenance, or autonomous systems.
• Blockchain-related inventions may be patentable if they provide tangible technical advantages such as improved security, tamper-proof data traceability, or enhanced data integrity within a defined technological environment.
• In the case of Quantum Computing, both quantum hardware and quantum algorithms are evaluated for their technical enablement and contribution to solving computation-intensive problems, particularly in optimization, encryption, or simulation.
• For IoT and Edge Computing, the emphasis lies on the interaction between physical devices and software, where the system's ability to deliver real-time responsiveness and adaptive behavior is considered a clear technical effect.

Overall, the guidelines stress that inventions in these domains must go beyond abstract theory or general-purpose computation and must show specific, technical implementation and benefit within a defined application space.

Clarification on the Role of Hardware

In the 2025 CRI Guidelines one thing is emphatically clear that allowability under section 3(k) does not necessitate presence of “Novel Hardware”. Rather presence of technical solution to technical problem through technical means and thereby achieving certain technical effects, which are beyond mere incidental effects, even when the same is achieved by implementation of computer programme, may lead the claimed invention to overcome exclusion under computer programme per se of section 3(k).

Comparative Analysis of the CRI Guidelines 2017 and 2025

The Indian Patent Office has evolved its approach toward examining Computer Related Inventions (CRIs) significantly between the 2017 and 2025 guidelines. The primary aim of both sets of guidelines remains the same: to ensure consistency in the examination process of CRIs while interpreting the legislative exclusions under Section 3(k) of the Patents Act, 1970. However, the 2025 guidelines are much more comprehensive, technologically updated, and jurisprudentially aligned with recent court decisions than their 2017 counterpart.

Broader Technological Context and Relevance

The 2025 Guidelines open with a robust and updated discussion of modern technologies that are reshaping innovation and industry, including artificial intelligence (AI), machine learning (ML), deep learning (DL), quantum computing, blockchain, Internet of Things (IoT), 5G/6G, cybersecurity, edge computing, and cloud infrastructure. These developments are viewed as catalysts for next-generation inventions. In contrast, the 2017 guidelines focused on traditional information technology systems and computer programmes without such detailed elaboration of emerging domains. The 2025 version integrates how these technologies demand rethinking of what constitutes technical contribution and how patent eligibility is determined.

Integration of Legal Trends in CRI Cases

One of the most notable upgrades in the 2025 Guidelines is the extensive incorporation of Indian court decisions that interpret Section 3(k). The 2017 guidelines, while outlining the legal framework, offered limited case law and did not reflect the evolving stance of Indian courts on software and algorithm-related inventions. The 2025 guidelines cite numerous judgments such as Ferid Allani v. Union of India, Microsoft Technology Licensing LLC v. Assistant Controller of Patents, Raytheon Company v. Controller General of Patents, and others. These cases collectively stress that inventions which produce a “technical effect” or solve a “technical problem” using software are not barred under Section 3(k), even when implemented on general-purpose computers.

Further, the CRI Guidelines 2025 incorporate evolving legal interpretations by referencing key judicial decisions that have shaped the understanding of Section 3(k). Annexure II provides illustrative case law excerpts that highlight how courts have assessed the patentability of computer-related inventions from multiple legal perspectives, offering clarity on the application of legislative provisions to modern technological contexts.

Recognition of Technical Effect and Contribution

The 2025 Guidelines make a strong case for determining patent eligibility of CRIs by applying the “technical effect” or “technical contribution” test. These concepts are central to evaluating whether a software-based invention transcends a mere abstract idea and contributes to the field of technology. Inventions involving two-factor authentication, enhanced data compression, or improved media processing are considered patentable if they go beyond a user-interface enhancement and address system-level functioning. The 2017 guidelines did not formally adopt this test, often resulting in stricter exclusions based merely on categorization rather than function or impact.

Section-Wise Expansion and Dedicated Technology Coverage

Another major difference is the inclusion of dedicated sections in the 2025 guidelines addressing specific technologies. Chapter 5 of the 2025 Guidelines is entirely devoted to examining patent applications in emerging areas such as AI/ML/DL, quantum computing, and blockchain. The examination strategies, exclusions, and considerations specific to these domains are separately discussed.

Revised Examination Framework and Practical Steps

The 2025 Guidelines introduce a refined and systematic approach for the Examiners and the Applicants to determine novelty, inventive step, industrial applicability, and sufficiency of disclosure. The guidelines reference a "Seven Stambhas Approach" laid out by the Honorable Delhi High Court for assessing novelty, and a five-step approach for determining inventive step. This structured methodology aims to reduce subjectivity and increase transparency in how the Examiners handle CRI applications. The 2017 guidelines, though broadly aligned with the Patents Act, lacked such structured decision-making protocols and were more general in guidance.

Harmonization with Global Practices

Finally, the 2025 Guidelines exhibit a deliberate attempt to align Indian examination practices with those of leading international patent offices (such as the EPO and USPTO). While preserving India’s legal specificity especially in the interpretation of “per se” the guidelines also integrate global best practices like the emphasis on technical problem-solving, inventive contribution, and practical application of the claimed invention. The 2017 guidelines did not demonstrate such harmonization, often leading to unpredictability and inconsistency in CRI patent examination.

Summary

The 2025 CRI Guidelines show a clear and improved approach to handling computer-related inventions. They include updated terms, court decisions, and detailed instructions for new technologies like AI, ML, blockchain, IoT, and quantum computing. The earlier 2017 Guidelines gave a basic structure, but the 2025 version offers better clarity and keeps up with current developments. By focusing on real technical contributions instead of just formal rules, the guidelines aim to support innovation while avoiding patents on simple ideas. They help the Examiners and the Applicants to work with more consistency, fairness, and alignment with global standards, making India’s patent system stronger and more modern.

Battle Between Chile and Peru Over Name of Alcoholic Beverage PISCO

Asociacion De Productores De Pisco A.G. v. Union of India & Ors.

[Contributors: Kevin A. Samuel and Anand Jakhar]

Recently, the Delhi H.C. allowed the writ of Chilian ASOCIACION DE PRODUCTORES DE PISCO A.G. to put “Peruvian” as a prefix before the GI product ‘PISCO’ in the register and set aside the order of the IPAB. The core of the dispute revolved around the geographical indication registration for "PISCO" as to whether it should be exclusively granted to Peru or if Chile also has a right to use the name, potentially as "Chilean PISCO" alongside "Peruvian PISCO".

In 2005, Respondent No. 4 (hereinafter referred to as Peru), representing Peruvian interests, applied for the GI "PISCO". The petitioner opposed this application in 2007, claiming shared rights over the GI "PISCO". The Registrar allowed the registration for Respondent No. 4 but with the caveat of registering it as "Peruvian PISCO" to avoid deception or confusion among consumers, acknowledging that both Peru and Chile were using "PISCO". Peru appealed this decision to the IPAB, which set aside the Registrar's order and held that Peru was entitled to the GI registration of "PISCO" without the "Peruvian" prefix.

The petitioner then filed the present writ petition challenging the IPAB's order and also filed its own GI application for "Chilean PISCO" on June 3, 2020.

The hon’ble Court noted that the Registrar initially granted "Peruvian PISCO" to avoid confusion, and it highlighted the purpose of the GI Act, which aims to protect producers, prevent misuse and deception, and promote goods with specific geographical origins, aligning with the TRIPS agreement.

The Court succinctly interpreted Section 10 of the GI Act and considered the present case as a homonymous registration. Crucially, the court agreed with the petitioner that "Chilean PISCO" and "Peruvian PISCO" are distinct products in terms of grapes used, distillation processes, and ageing. It cited sources stating that "homonymous geographical indications are those that are spelt or pronounced alike but which identify products originating in different places, usually in different countries" and that such indications should coexist, possibly with additional information to prevent misleading consumers.

The Court firmly distinguished between the scope of coverage of a GI and a trademark while rejecting Peru's arguments of "prior use" and alleged "historical misappropriation" of the term by Chile. It noted that the fact that Peru has a city called Pisco is irrelevant to the enquiry when admittedly all Pisco in Peru isn't made there, and the word has zoological and ethnographic origins in the Quechua language.

The court ruled that shared history between the countries is sufficient to acknowledge that the beverage comes from both geographies, and a shared production region that is contiguous is not a precondition. While interpreting Sections 9 (a), (g) and 10 of the GI Act harmoniously, it observed that allowing Peru to enjoy an exclusive right over Pisco as a GI would not only cause consumer confusion given that the Chilean beverage is also called Pisco but would also adversely affect the rights of Chilean producers.

The court further found that the IPAB's finding that the name ‘PISCO’ cannot be identified as Chilean or Peruvian, as the liquor produced by both countries are totally different, was erroneous, as the qualitative difference does not negate the fact that the Chilean beverage is also identified as ‘PISCO’.

INDIA IP NEWS & DEVELOPMENTS

• On July 23, 2025, the Delhi High Court directed Lava International to deposit ₹20 crore as interim security in an ongoing case filed by Dolby Laboratories. The court’s order reflects India’s growing emphasis on SEP enforcement and fair licensing practices in high-tech sectors. READ MORE
• The Supreme Court has ruled that companies can be considered victims under the Code of Criminal Procedure, allowing them to appeal acquittal orders in cases like intellectual property rights violations. READ MORE
• In a significant anti-counterfeiting action, Delhi Police and Authorized Representative from Honda Motorcycle & Scooter India Pvt. Ltd. successfully raided a business in Sarai Rohilla, New Delhi seizing a substantial cache of counterfeit Honda two wheeler parts. READ MORE
• The Delhi High Court recently set aside the Controller’s decision rejecting Coca-Cola’s patent application for a beverage dispenser in the case of ‘The Coca-Cola Company v. The Controller of Patents & Anr.’, holding that the refusal order was merely issued on the grounds of lack of inventive step without adequate consideration. READ MORE

WORLD IP NEWS & DEVELOPMENTS

• U.S. senators blasted companies, including Meta and Anthropic, for training AI models on copyrighted content, including pirated books and other materials. The U.S. Copyright Office warned not all AI training falls under fair use and recommended creating a licensing system for generative AI content. READ MORE
• On July 22, 2025, China’s National Intellectual Property Administration (CNIPA) published draft guidelines to improve IP support for private businesses and enhance global competitiveness. The proposal includes faster patent and trademark examination, robust IP legal services, overseas risk monitoring, and stronger dispute mediation mechanisms. READ MORE
• The WTO Appeal Arbitrator ruled on July 21, 2025, that China’s court-issued anti-suit injunctions, blocking foreign patent enforcement, violate TRIPS rules, reversing a previous 2022 panel decision. READ MORE
• India and the United Kingdom have concluded the Comprehensive Economic and Trade Agreement (CETA) in London, encompassing digital trade, public procurement, and notably, intellectual property regulations. READ MORE

PATENTLY ABSURD

• Banana Protective Device (US6612440B1): The banana protective device (US 6612440 B1), patented in 2003, is a uniquely shaped case designed specifically to store and transport a banana safely. The invention consists of two hinged, banana‑shaped plastic shells that enclose the fruit. Inside, foam pad members securely cushion the banana, preventing bruises or squash damage, while hook‑and‑loop fasteners (similar to Velcro) keep the case tightly closed. The shells also feature ventilation perforations to allow airflow and reduce moisture buildup. Compact, reusable, and inexpensive to manufacture, it offers a simple yet effective solution to protecting bananas during everyday transport.

• Body-worn device for dance simulation (US9000899B2): This patent discloses a wearable belt-like device equipped with tactile feedback actuators positioned on opposite sides of the torso—one on the chest and one on the back. Each actuator delivers programmed pressure cues simulating social dance contact (e.g. chest‑to‑chest or hand‑to‑back), controlled wirelessly via a communication channel. The device also incorporates motion sensors to detect the user's movement, which is transmitted to a logic module that determines appropriate tactile feedback.

BRIEF OVERVIEW ON EMERGING TECHNOLOGIES

Neuromorphic Computing and Artificial Intelligence

Introduction:

Neuromorphic computing is an approach to computing that mimics the way the human brain works. It entails designing hardware and software that simulates the neural and synaptic structures and functions of the brain to process information. In other words, the neuromorphic computing is a branch of computer engineering in which elements of a computer are modelled after systems in the human brain and nervous system. The term refers to the design of both hardware and software computing elements.

How it works:

Neurons are the fundamental units of the brain and nervous system. As messengers, these nerve cells relay information between different areas of the brain and to other parts of the body. When the neuron becomes active or “spikes,” it triggers the release of chemical and electrical signals that travel via a network of connection points called synapses, allowing neurons to communicate with each other.

These neurological and biological mechanisms are modelled in neuromorphic computing systems through spiking neural networks (SNNs). The spiking neural network is a type of artificial neural network which is composed of spiking neurons and synapses. In biological systems, synapses change their strength (how strongly a signal is passed from one neuron to another) based on the activity of the pre and post synaptic neurons.

Further, the spiking neurons store and process data similar to biological neurons, with each neuron having its own charge, delay and threshold values. The synapses further create pathways between neurons and also have delay and weight values associated with them. These values are neuron charges, neuron and synaptic delays, neuron thresholds and synaptic weights and all can be programmed within neuromorphic computing systems.

In neuromorphic architecture, synapses are represented as transistor-based synaptic devices, employing circuits to transmit electrical signals. By way of example, the synapses include a learning component, altering their weight values over time according to activity within the spiking neural network. The learning component refers to the mechanism or rule by which the strength (or weight) of the synapse changes over time based on the activity between neurons. The activity between neurons is depicted by mimicking the way the neurons communicate — using spikes, or discrete electrical pulses — instead of continuous signals like in traditional artificial neural networks.

Therefore, the neuromorphic computing is a paradigm shift in how we design and interact with intelligent systems. By mimicking the architecture and operational principles of the human brain, neuromorphic systems offer the promise of low-power, high-efficiency processing ideally suited for real-time, adaptive tasks. From edge AI applications to robotics and sensor networks, the potential for transformative impact is vast.

The impact on AI and beyond

The neuromorphic computing is expected to change many current AI technologies by saving power and improving performance in ways that current AI chips cannot. Early uses include detecting events, recognizing patterns, and training with small datasets. These abilities help AI systems handle the unpredictability of the real world, making them more robust and adaptable.

Additionally, it makes product development easier, allowing tech enthusiasts to create AI systems that quickly respond to real-time events and information. This will lead to many future AI products, like autonomous drones and advanced robots.

For example, driverless cars are often considered dangerous because they can't react as quickly as humans in split-second situations. Tesla tried to solve this problem to avoid hitting obstacles on the road, but it failed in one case when a Tesla vehicle hit a deer and kept going because its AI didn't see the danger.

Neuromorphic computing will help solve these kinds of problems in the near future.

Neuroscience research: Neuromorphic computing can aid in neuroscience research by providing a platform to simulate and study brain functions, leading to a better understanding of neurological disorders and the development of new treatments.

Examples:

Neuromorphic processors include Loihi from Intel, NeuronFlow from GrAI Matter Labs and the TrueNorth and next-generation NorthPole neuromorphic chips from IBM®. Most neuromorphic devices are made from silicon and use CMOS (complementary metal-oxide semiconductor) technology.

Common learning rules (learning components) in SNNs:

STDP (Spike-Timing-Dependent Plasticity):

• If a presynaptic neuron fires just before a postsynaptic neuron, the synaptic weight increases (potentiation).
• If it fires after, the weight decreases (depression).
• This captures a biological principle often summarized as "neurons that fire together, wire together.

Hebbian learning:

• A more general principle: if two neurons are active at the same time, the connection between them strengthens.

Reward-modulated STDP:

• Combines timing-based learning with reinforcement signals (rewards or penalties) to guide learning.

NEUROMORPHIC COMPUTING ARCHITECTURE IN SMART AGRICULTURE

An example of implementation area of the neuromorphic computing architecture can be in smart agriculture. Figure 1 shows an architecture of the smart agriculture, biological computing, and neuromorphic computing. With the development of the IoT, many kinds of smart devices such as smart sensors, wireless transmission, drones, and remote centers have been used to realize unmanned, automated, and intelligent management in agriculture. The different kinds of agricultural parameters could be sensed by the sensors. The sensors could be deployed and wirelessly transmitted to the remote center for further processing, artificial intelligence analysis, and decision making.

However, this mode is based on the conventional von Neumann architecture. The smart system needs more memory, a fast computing central processing unit, and high energy consumption. Therefore, the neuromorphic computing in smart agriculture as proposed is shown in Figure 1.

As explained earlier, the neuromorphic computing uses non-spike artificial neural networks (ANNs) such as the convolutional neural network (CNN) and the spike neural network (SNN) to perform the computational tasks.

To elaborate further, in smart agriculture, the agricultural parameters such as the humidity, temperature, light, sound, pressure, and gas in smart agriculture could be regarded as the tactile, visual, auditory, olfactory, and gustatory information which corresponds to the human biological systems.

The neuromorphic computing in smart agriculture consists of sensors, artificial synapses, artificial neurons, and an ANN. The sensors in smart agriculture could sense the agricultural parameter information in actual situations, and transmit it to the artificial synapses after the spike encoding. The artificial neurons receive the spike signals and transmit them to the ANN for further processing, training, learning, and computing so that the farmers could manage the smart agriculture with fast, low-cost, low-energy consumption to improve the production efficiency.

For example:

Artificial Visual System: The application of digital imaging technology in smart agriculture may utilize humidity, temperature, light, sound, and gas. This covers multiple aspects from monitoring the agricultural environment and identifying pests and diseases to the automated processing of agricultural machinery, significantly improving the efficiency and quality of agricultural production.

In another example, the pressures in smart agriculture are mostly focused on the harvesting and processing phases. The pressure information needs to be monitored in real time to ensure the precise control of the picking and avoid damage to the agricultural products such as apples, pears, avocados, kiwifruit, and strawberries during the picking and harvesting phase, and the precise control of the grasping and the quality sensing of agricultural products such as fish, meat, and fruits on the processing assembly line during the processing phase by the smart agricultural robots as shown in Figure 3b-3e.

For in-depth understanding refer to the citations below:

• Neuromorphic Computing for Smart Agriculture
• Neuromorphic computing
• Neuromorphic Computing and Engineering with AI
• Neuromorphic computing: The future of AI and beyond

Smart Contact Lens: The Future of Augmented Reality

Introduction:

Smart contact lenses are a developing technology that integrates electronic components and sensors into contact lenses to provide functionalities beyond vision correction. The Smart Contact Lens is an innovative approach that has the potential to completely transform augmented reality (AR) in the rapidly changing field of wearable technology. These lenses can monitor health metrics, deliver medication, and even offer augmented reality experiences. While some applications are already in use, others, like augmented reality, are still under development. The wearable, ultra-low-power AR smart contact lens blends the digital and real worlds seamlessly and hands-free. It fits directly into your eye. The smart contact lens is nearly undetectable, which gives users a more distinct and natural way to experience AR content than traditional AR devices like smart glasses or headsets. Without requiring heavy hardware, this technology creates new opportunities in information access, navigation, and healthcare.

What are Smart Contact Lens?

The smart contact lens provides real-time information without being intrusive on the user's regular activities. The smart contact lens is not thicker than a typical soft contact lens and houses a variety of sensors, an onboard processor, and a tiny micro-LED display.

The lens provides hands-free, intuitive, and immersive interaction by projecting AR data directly onto the user's retina through a tiny, transparent display. Through Bluetooth, the contact lens connects to smartphones or other devices, allowing users to access media, health information, notifications, and navigation prompts without ever looking at a screen.

Functionalities:

A micro-LED display built into the smart contact lens can project high-resolution text, graphics, and images straight onto the user's retina. Blending digital data with the physical world produces an immersive augmented reality experience.

• Smartphone Integration: The smart contact lens uses Bluetooth to connect to mobile devices. This enables hands-free access to information without requiring the user to reach for a device by retrieving data from the user's smartphone's apps, notifications, or GPS systems.
• Health and Wellness Monitoring: The smart contact lens may be able to track a user's vital signs, including body temperature, heart rate, and movement, providing a seamless, inconspicuous health monitoring system. Additionally, this might pave the way for medical applications in which physicians could remotely and in real time monitor the health of their patients.
• The smart contact lens provides hands-free, intuitive, and immersive interaction by projecting AR data directly onto the user's retina through a tiny, transparent display. Through Bluetooth, the contact lens connects to smartphones or other devices, allowing users to access media, health information, notifications, and navigation prompts without ever looking at a screen.
• Inbuilt Sensors: The smart contact lens can recognize head and eye movements using a gaze-tracking system, motion sensors, and accelerometers. This provides a genuinely hands-free experience by enabling users to navigate virtual interfaces using basic eye gestures.
• Ultra-Low Power Consumption: The ultra-low power consumption of the smart contact lens is one of its best qualities. In contrast to other wearables, the lens can be made to function well for a full day on a single charge, which is crucial for the user's comfort and usefulness.

How It Operates: Practical Uses

An ultra-low-power augmented reality image is projected directly onto the user's retina by the Smart Contact Lens, which functions by integrating a micro-LED display into the lens. An onboard processor powers this display, which is Bluetooth-enabled to an external device (such as a smartphone or AR controller). The user can interact with the displayed content by simply changing their focus or blinking, recognizing a combination of motion sensors and eye-tracking technology that interprets their blinks.

Consider an example, negotiating a crowded city street. Turn-by-turn directions could be projected onto your vision as you walk by wearing the smart contact lens, making it simpler to follow without needing to look at a phone or put on heavy AR glasses. The lens might also show health information in a real-world trial, such as heart rate, real-time glucose monitoring (for diabetics), or even subtitles for conversations in other languages. In addition, the lens could subtly show important details or reminders during a meeting while remaining entirely unobtrusive to others around you. The goal is to deliver context-sensitive, invisible information when you need it without interfering with your natural environment.

Hands-on Experience:

Even though the smart contact lens is still in the early stages of development, a number of interactive demonstrations and prototype tests have provided professionals and tech enthusiasts with a preview of what lies ahead. According to the testers and users, the lens is comfortable and lightweight, almost identical to a conventional contact lens. According to reports, the AR display is clear and sharp, with the virtual overlay standing out against the actual background. The technology's ease of use is among its most fascinating features. It seamlessly integrates into daily life by allowing you to interact with apps, navigate menus, and even receive notifications with just eye movements.

The Smart contact lens is far more useful than the majority of other AR devices due to its low power consumption and all-day wear. Bulky hardware won't interfere with or hinder users' ability to carry out their daily tasks.

Example of the Smart Contact Lens:

Mojo Vision Lens: An innovative development in smart contact lens technology is the Mojo Vision Lens. By incorporating a micro-LED display straight into a contact lens, users can view digital data projected on their field of vision. Wearable technology and augmented reality (AR) combine to provide real-time data without requiring external devices like smartphones or smartwatches, making the experience genuinely hands-free. With the help of the lens's eye-tracking technology, users can manipulate what they see with just eye movements. This could entail seeing fitness metrics, getting notifications, or finding your way around.

The Mojo Vision lens can continue to function without the need for physical connections thanks to wireless charging, and it easily syncs with other devices to update data. Mojo Vision is currently concentrating on augmented reality and health applications, but as the technology develops, its use cases are probably going to spread into sectors like social media, retail, and education, improving our interactions with the digital world.

Important uses include navigation, which provides directions without requiring a screen view, and health tracking, which allows users to track their steps or heart rate in real time. It has the potential to transform how we engage with digital content in industries like education, healthcare, and entertainment. The Mojo Vision Lens, which combines convenience, usefulness, and cutting-edge technology to bring augmented reality to the most personal and commonplace of wearables, the smart contact lens.

Real-World Test:

• In 2022, Drew Perkins, CEO of Mojo Vision, achieved a significant milestone by becoming the first individual to wear a fully integrated smart contact lens prototype in his eye. Through the lens, he was able to view actual data in real time, proving that the display, sensors, battery, and communication could all function together securely and efficiently. Mojo Vision's lens was the first real AR contact lens prototype ever tested on a human, demonstrating that the idea was more than just science fiction. The accomplishment represents a significant step toward wearable AR that is invisible, user-friendly, and integrated into daily life.
• Using AR to Help with Urban Navigation: Mojo Vision also conducted an experiment in which participants were asked to use the smart contact lenses in a normal everyday setting as part of a real-world demonstration. Navigating a busy city while walking was one of the most interesting scenarios.

A set of turn-by-turn instructions were placed directly in the field of view of a user wearing the Mojo Vision lens as they navigated through the heart of the city. The lens ensured that the user could stay on course without needing to wear a heavy device or check a smartphone screen by superimposing clear, real-time visual cues for every turn. Because they didn't have to pull out a phone or stop to stare at a screen, testers said that having the directions in their direct line of sight made the experience more natural and hands-free. Another highlight was the lens's real-time responsiveness, which provided context-sensitive information about the user's surroundings by adjusting according to their location and gaze direction.

An additional example from the experiment demonstrated how sports activities could make use of health monitoring features. The smart contact lens provided a smooth integration of fitness tracking without the need for a smartwatch or fitness band by monitoring the user's heart rate and step count while they ran and displaying these metrics in the corner of their vision.

Future Scope:

• Applications in Health and Medicine: Smart Contact lenses have huge potential in the healthcare industry, in addition to entertainment and productivity. Physicians could deliver better, individualized care if they could monitor a patient's health data. Also, real-time vision enhancements could improve the quality of life for patients with visual impairments.
• Including AI and Machine Learning: The smart contact lens may get even smarter as AI and machine learning technologies advance. Imagine a time in the future when the lens can anticipate your needs, learn your preferences, and give you context-sensitive, real-time information. For example, it might offer real-time translations when you're travelling overseas, abroad, offer suggestions for routes during your commute, or give you information about the places you visit.
• Potential in Entertainment & Gaming: The smart contact lens has the potential to revolutionise the gaming industry. Imagine interactive media experiences that superimpose virtual elements on your surroundings or immersive games that react to your eye movements, all without the need for bulky controllers or headsets.

Conclusion:

The newest advancement in wearable technology is the Smart Contact Lens. Augmented reality opens up a world of possibilities that could completely change the way we interact with digital information by being seamlessly incorporated into daily life. Despite being in its infancy, the smart contact lenses have a lot of potential, especially in the fields of entertainment, navigation, and health. As the technology develops, it might be adopted more widely, expanding the use of augmented reality into new domains and transforming not only wearables but also how we interact with and perceive the world. The future of smart contact lenses in augmented reality is undoubtedly bright, if the practical demonstrations are any guide. However, the smart contact lenses bring both excitement and uncertainty along the way.

References:

• What are Smart Contact Lenses?
• High-Tech Contact Lenses That Go Beyond Correcting Vision
• Advancements and applications of smart contact lenses: A comprehensive review
• Innovations in Contact Lens Technology: A Visionary Future
• Hands-on: Mojo Vision’s Smart Contact Lens is Further Along Than You Might Think
• CEO test-drives Mojo Vision's smart augmented reality contact lens
• The Future of Vision: Exploring Augmented Reality Contact Lenses
• Smart Contact Lenses: You Can Control a Micro LED Display with a Flick of Your Eyes
• Eye tracking: Smart Contact Lens
• VR/AR Contact Lens of the Future | Mojo Vision Lens

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