Volume 13 | Issue 2 |

 Abstract

Overview of the Digital Personal Data Protection Act 2023 Alamelu Guest Faculty Business Law Tamil Nadu Dr. Ambedkar Law University, Chennai, India This study has been undertaken to analyse the object and purpose of the Indian Digital Personal Data Protection Act 2023. It further analyses the provisions of the Act such as the definition of key terms, right and obligations of the Data Principal and Duties of Data Fiduciary under the Act. The analytical framework contains: Table of Contents 1. Introduction 2. Object and Purpose of the Act 3. History of India Digital Personal Data Protection Act 4. Key Definitions 4.1 Personal Data 4.2 Data Principal 4.3 Data Fiduciary 4.5 Data Processor 5 Scope and Applicability 6 Rights of Data Principal 6.1 Right to access information about personal data 6.2 Right to correction and erasure of personal data 6.3 Right of grievance redressal 6.4 Right to nominate 7 Duties of Data Principal 8 Obligations of Data Fiduciary 9 Processing of Personal Data of a children 9.1 Consent Requirement 9.2 Well-being protection 9.3 Restriction on tracking and advertising 9.4 Exemption 9.5 Government Notification 10 Processing Personal Data outside India 11 Data Protection Authority 12 Penalties 13 Conclusion Introduction: The Indian Digital Personal Data Protection Act 2023 (DPDP Act)1 represents a significant milestone in India's journey towards robust data protection and privacy regulations. It represents a landmark development in India's legislative landscape, aimed at fortifying the protection of personal data in an increasingly digital world. This legislation aims to safeguard the personal data of individuals while balancing the needs of businesses and the government. Here is a comprehensive overview of the key aspects of the DPDP Act and elucidating its key provisions, principles, and implications. The DPDP Act was enacted in response to escalating concerns over data privacy and the absence of a robust legal framework to safeguard personal data in India. The DPDP Act is inspired by global standards, such as the European Union's General Data Protection Regulation (GDPR) and from China's Personal Information Protection Law (PIPL)2, yet it is tailored to address the unique socio-economic and technological landscape of India. The enactment of this legislation marks a significant stride towards aligning India with international data protection norms, thereby enhancing its global standing in the digital economy. Object and Purpose of the DPDP Act The primary object of the Digital Personal Data Protection Act is to provide a robust legal framework for the protection of personal data in the digital environment. This includes: Safeguarding Personal Data: Ensuring that personal data is collected, processed, stored, and shared in a manner that protects the privacy and rights of individuals. Regulating Data Processing: Establishing clear guidelines and standards for the lawful processing of personal data by data controllers and processors. Empowering Individuals: Granting individuals greater control over their personal data, including rights to access, correct, and delete their data. Promoting Transparency: Mandating transparency in data processing activities, ensuring that individuals are informed about how their data is being used. Ensuring Accountability: Holding data controllers and processors accountable for their data processing activities, including compliance with the DPDP Act and any associated regulations. Protecting Privacy: To protect the fundamental right to privacy of individuals by ensuring that their personal data is handled with care and respect. Fostering Trust: To build and maintain trust in digital services and technologies by ensuring that personal data is processed in a secure and transparent manner. Facilitating Innovation: To create a balanced regulatory environment that allows for innovation and growth in the digital economy while safeguarding personal data. Harmonizing Standards: To align with international data protection standards and best practices, facilitating cross-border data flows and cooperation. Enhancing Security: To enhance the security of personal data by implementing stringent data protection measures and protocols. Providing Remedies: To provide individuals with effective remedies and recourse in the event of data breaches or violations of their data protection rights. History of India Digital Personal Data Protection Act Before 2022, India lacked a comprehensive privacy law. In 2017, the Supreme Court of India acknowledged the right to privacy as a constitutionally protected right in the "Puttaswamy judgement"3 also known as the Right to Privacy verdict. The court also highlighted India's absence of a comprehensive privacy law and the limitations of the existing Information Technology (Reasonable Security Practices and Procedures and Sensitive Personal Data or Information) Rules, or SPDI Rules, which were implemented in 2011. Following the Right to Privacy verdict, the Indian government developed draft legislation aimed at protecting the privacy of Indians. Earlier versions of the Personal Data Protection Bill faced significant scrutiny and were ultimately unsuccessful, including the Data Protection Bill 2021, which bore some similarities to the European Union's General Data Protection Regulation (GDPR). This bill was withdrawn in August 2022. On November 18, 2022, the Ministry of Electronics and Information Technology proposed the Digital Personal Data Protection Bill 2022. This bill was intended to replace certain parts of existing law (Section 43A of the IT Act) and the SPDI Rules4 and was finalized as India's Digital Personal Data Protection Act (DPDP Act) when it received approval from both houses of Parliament and the assent of the President in August 2023. The law came into effect August 11, 2023 and covers personal data collected in digital format, or collected by other means and later digitized. Key Definitions Personal Data "Personal data" means any data about an individual who is identifiable by or in relation to such data.5 Any information that relates to an identified or identifiable individual. Data Principal "Data Principal" means the individual to whom the personal data relates and where such individual is-- (i) a child, includes the parents or lawful guardian of such a child; (ii) a person with disability, includes her lawful guardian, acting on her behalf.6 The term "Data Principal" refers to the individual to whom the personal data pertains. This definition encompasses specific considerations for certain groups of individuals. When the Data Principal is a child, the term extends to include the parents or lawful guardian of the child. This means that the parents or lawful guardian are considered the Data Principal in relation to the child's personal data. When the Data Principal is a person with a disability, the term includes her lawful guardian who acts on her behalf. This ensures that the lawful guardian is recognized as the Data Principal in matters concerning the personal data of the person with a disability. The definition of "Data Principal" is inclusive, ensuring that children and persons with disabilities are represented by their lawful guardians in matters related to their personal data. Data Fiduciary "Data Fiduciary" means any person who alone or in conjunction with other persons determines the purpose and means of processing of personal data.7 Any person, including the State, a company, any juristic entity, or any individual who alone or in conjunction with others determines the purpose and means of processing personal data. Essentially, a Data Fiduciary is responsible for the collection, storage, and processing of personal data and must ensure that these activities are conducted in compliance with the provisions of the DPDP Act. Few examples of Data Fiduciary: Tax Authorities: Collect and process personal data for tax assessment and collection. E-commerce Websites: Platforms like Amazon and Flipkart collect and process personal data for online shopping and transactions. Banks: Collect and process personal data for account management, loans, and other financial services. Hospitals and Clinics: Collect and process personal data for patient care and medical records, etc. Data Processor "Data Processor" means any person who processes personal data on behalf of a Data Fiduciary.8 A data processor is an entity or individual who processes personal data on behalf of a data fiduciary. The data processor does not own the data but handles it according to the instructions and purposes defined by the data fiduciary and within the legal framework of the DPDP Act. Few examples of Data Processors: - Cloud service providers who store data on behalf of a company. - Third-party analytics firms that analyse data for another organization. - Payroll companies that manage employee data for other businesses. Scope and Applicability The DPDP Act applies to the processing of digital personal data within the territory of India where the personal data is collected in (i) digital form; or (ii) non-digital form and digitized subsequently. It applies to the processing of digital personal data within India, and to data fiduciaries and data processors outside India if they process personal data in connection with any business carried out in India, or if they offer goods or services to data principals within India. DPDP Act does not apply to an individual who processes such personal data for any personal or domestic purpose. This means that activities such as maintaining a personal address book, family photo albums, or personal correspondence are exempt from the regulations. DPDP Act does not apply to data made publicly available by the data principal themselves or by law. Rights of Data Principal The DPDP Act grants several rights to data principals, empowering individuals to have greater control over their personal data. Right to access information about personal data: The Data Principal, who has previously given consent to a Data Fiduciary for the processing of their personal data, has the right to request certain information from that Data Fiduciary. Upon making a request in the prescribed manner, the Data Principal can obtain: (a) a summary of the personal data being processed and the processing activities undertaken by the Data Fiduciary; (b) the identities of all other Data Fiduciaries and Data Processors with whom the personal data has been shared, along with a description of the shared data; and (c) any other prescribed information related to their personal data and its processing. However, the requirements to provide information under clauses (b) and (c) do not apply if the personal data is shared with another Data Fiduciary authorised by law for purposes such as the prevention, detection, investigation, prosecution, or punishment of offences or cyber incidents, provided the request for such data sharing is made in writing. Right to correction and erasure of personal data: A Data Principal has the right to request the correction, completion, updating, and erasure of her personal data, for which she has previously given consent, in accordance with applicable laws. Upon receiving such a request, a Data Fiduciary must correct the inaccurate or misleading data, complete the incomplete data, and update the personal data. For erasure requests, the Data Fiduciary must erase the data unless it is necessary to retain it for specified purposes or legal compliance. Right of grievance redressal: the Data Principal is entitled to grievance redressal mechanisms provided by the Data Fiduciary or Consent Manager for any issues related to personal data handling. The Data Fiduciary or Consent Manager must respond to grievances within a prescribed period, and the Data Principal must exhaust these grievance mechanisms before approaching the Board. Right to nominate: the Data Principal can nominate another individual to exercise her rights in the event of her death or incapacity, defined as the inability to exercise her rights due to unsoundness of mind or physical infirmity. Duties of Data Principal A Data Principal is required to adhere to several duties, including complying with all applicable laws while exercising their rights under the DPDP Act. They must not impersonate others when providing personal data for specified purposes and should avoid suppressing any material information when submitting personal data for documents or identifiers issued by the State. Additionally, they should refrain from registering false or frivolous grievances or complaints with a Data Fiduciary or the Board. Lastly, they must ensure that any information provided for correction or erasure is verifiably authentic. Obligations of Data Fiduciary Data Fiduciaries have several obligations under the DPDP Act to ensure the protection of personal data. A person may process the personal data of a Data Principal only in accordance with the provisions of the DPDP Act and for a lawful purpose, which includes obtaining the Data Principal's consent or for certain legitimate uses. A lawful purpose is defined as any purpose not expressly forbidden by law. Requests for consent must be accompanied or preceded by a notice from the Data Fiduciary, detailing the personal data to be processed, the purpose, the Data Principal's rights, and the complaint process. The consent given by the Data principal must be free, specific, informed, unconditional, and unambiguous with a clear affirmative action, and the Data Principal has the right to withdraw consent at any time. The Data Fiduciary must cease processing the data upon withdrawal of consent unless otherwise required by law. Consent can be managed through a Consent Manager, who must be registered and accountable to the Data Principal. Every Consent Manager shall be registered with the Board in such manner and subject to such technical, operational, financial and other conditions as may be prescribed. The Data Fiduciary must prove that proper notice was given by her to the Data Principal and consent were obtained from such Data Principal to the Data Fiduciary if questioned in a proceeding in this regard. Data Fiduciary is accountable to the Data Principal and irrespective of any agreement to the contrary or failure of a Data Principal to carry out the duties provided under DPDP Act, she must implement appropriate measures to ensure compliance with the DPDP Act. The Significant Data Fiduciary, any Data Fiduciary or class of Data Fiduciaries as may be notified by the Central Government, conduct assessments called "Data Protection Impact Assessments" for processing activities that pose a high risk to data principals rights and freedoms. Data Fiduciary must notify the Data Protection Authority and affected data principals in the event of a data breach. Data Fiduciary may appoint Data Processor to process personal data on its behalf for any activity related to offering of goods or services to Data Principals under a valid contract. Processing of Personal Data of a children Consent Requirement Before processing the personal data of a child or a person with a disability who has a lawful guardian, a Data Fiduciary must obtain verifiable consent from the parent or lawful guardian. Well-being Protection A Data Fiduciary must avoid processing personal data in ways that could harm a child's well-being. Restrictions on Tracking and Advertising Data Fiduciaries are prohibited from tracking, behaviorally monitoring, or targeting advertising at children. Exemptions Certain classes of Data Fiduciaries or specific purposes may be exempted from the requirements of obtaining consent and restrictions on tracking and advertising, as prescribed. Government Notification The Central Government can exempt a Data Fiduciary from some obligations if it is satisfied that the Data Fiduciary processes children's data in a verifiably safe manner, specifying an age above which the exemptions apply. Processing Personal Data outside India The Central Government has the authority to restrict the transfer of personal data by a Data Fiduciary to specific countries or territories outside India through a notification. However, it does not override any existing Indian laws that offer a higher level of protection or impose stricter restrictions on the transfer of personal data by a Data Fiduciary outside India. These existing laws will continue to apply to any personal data or Data Fiduciary, or class thereof, ensuring that the highest standards of data protection are maintained. Data Protection Authority The DPDP Act 2023 establishes that the Central Government may, by notification, appoint, for the purposes of this DPDP Act, a Board to be called the Data Protection Board of India (DPBI) responsible for overseeing the implementation and enforcement of the DPDP Act. The DPBI has the power to: - Monitor and enforce compliance with the DPDP Act - Investigate data breaches and complaints - Impose penalties for non-compliance - Issue guidelines and codes of practice Penalties Failure to adhere to the requirements of the DPDP Act, particularly the breach of essential information security measures necessary to reduce the risk of a personal data breach, may result in fines reaching 250 crore INR ($30 million). This penalty is less stringent than the 2022 legislation, which suggested fines of up to 500 crore INR (approximately $61 million). Conclusion The Indian Digital Personal Data Protection Act 2023 is a pivotal piece of legislation that aims to fortify data privacy and protection in India. By establishing clear guidelines and robust enforcement mechanisms, the DPDP Act seeks to build trust in the digital ecosystem and ensure that personal data is handled with the utmost care and responsibility. As businesses and individuals navigate the new regulatory landscape, the DPDP Act 2023 will play a crucial role in shaping the future of data protection in India. References 1. https://www.meity.gov.in/writereaddata/files/Digital%20Personal%20Data%20Protection%20Act%202023.pdf 2. https://usercentrics.com/knowledge-hub/india-digital-personal-data-protection-act dpdpa/#:~:text=The%20DPDP%20Act%20is%20a,to%20control%20and%20protect%20it. 3. Puttaswamy V Union of India, SC, 2017 (10) 4. https://www.digitalguardian.com/blog/what-indias-digital-personal-data-protection-dpdp-act-rights-responsibilities-everything-you. 5. Section 2 (t) of the DPDP Act. 6. Section 2 (j) of the DPDP Act 7. Section 2 (i) of the DPDP Act 8. Section 2(k) of the DPDP Act The information contained in this site is general in nature and should not be considered to be legal, tax accounting, consulting or any other professional advice. In all cases you should consult with professional advisors familiar with your particular factual situation for advice concerning specific matters before making any decisions.

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overview, digital personal data protection

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Demand forecasting is an important task for retailers as it is required for various operational decisions. One key challenge is to forecast demand on special days that are subject to vastly different demand patterns than on regular days. We present the case of a bakery chain with an emphasis on special calendar days, for which we address the problem of forecasting the daily demand for different product categories at the store level. Such forecasts are an input for production and ordering decisions. We treat the forecasting problem as a supervised machine learning task and provide an evaluation of different methods, including artificial neural networks and gradient-boosted decision trees. In particular, we outline and discuss the possibility of formulating a classification instead of a regression problem. An empirical comparison with established approaches reveals the superiority of machine learning methods, while classification-based approaches outperform regression-based approaches. We also found that machine learning methods not only provide more accurate forecasts but are also more suitable for applications in a large-scale demand forecasting scenario that often occurs in the retail industry.advancements.

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ML

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Abstract-Creating an efficient and error-free timetable is a critical yet challenging task for educational institutions, often requiring significant manual effort and prone to scheduling conflicts. This paper presents an automated timetable scheduler designed to streamline the scheduling process in colleges. The system generates timetables automatically by taking subjects, faculty names, and specific constraints as input.The primary objective is to reduce the time and effort required for timetable generation while ensuring conflict-free scheduling that adheres to predefined constraints, such as faculty availability and subject requirements. The proposed system employs constraint satisfaction algorithms and a rule-based approach to generate optimized timetables.The methodology integrates a user-friendly interface for data input and employs backend algorithms to allocate slots efficiently. Key findings demonstrate that the system can produce accurate and scalable timetables within minutes, significantly reducing manual workload. The system also includes features for administrators to manage events and reschedule lectures when necessary.This solution holds the potential to enhance college administration by automating a traditionally time-intensive process, ensuring accuracy, and allowing flexibility for future enhancements, such as multi-campus scheduling or integration with attendance tracking systems.

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Automated Scheduling, Conflict-free Scheduling, Timetable Management, Faculty Availability

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Pipes are common profiles in steel structures. These sections can be found in trusses, either chord or web members. Steel pipes can be connected by a single gusset plate, based on strength that can be calculated using available design rules in different guidelines. A new connection can be offered using two parallel plates which leads to higher strength. This connection subjected to normal load is examined in this paper. A finite element analysis is used to explore the effects of some factors on the strength of this connection.

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Steel pipe, Web-member, Two-plates.

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This paper presents a theoretical extension of AI- based attendance management systems by analyzing the limitations of traditional face recognition models and proposing advancements in deep learning-based models, liveness detection, and privacy-preserving AI. Existing attendance tracking methods, such as manual roll-call, RFID-based tracking, and fingerprint recognition, have limitations in accuracy, security, and usability. This research investigates how modern deep learning techniques, Edge AI, and blockchain integration can enhance recognition accuracy and scalability while ensuring data privacy. Future directions in AI-driven biometric attendance systems are also discussed.

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AI-Based Attendance, Face Recognition, Deep Learning, Edge AI, Liveness Detection, Blockchain, Privacy- Preserving AI, Federated Learning, AI Bias Mitigation.

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As a term, exaggeration refers to "a statement or description that makes something seem larger, better, worse or more important than it really is" (Oxford Advanced Lerner's Dictionary, 2006: 503). Exaggeration is very common in various languages; in addition to that, it is regularly and widely used in different genres including the genre of proverbs and sayings where it is a genre that represents the culture and the heritage of nations in brevity and with wisdom. For instance, when saying the English proverb, "Harm seek harm find", this proverb involves the using of repetition of the noun (harm) as amorphological technique expressing exaggeration. However, such exaggerated proverbs reveal a deep wisdom in words that are decorated with various morphological techniques that characterize them, including word repetition, reduplication and comparative and superlative forms. Accordingly, proverbs in English, are regarded as appropriate data to explore the exaggeration expressions in them morphologically. Hence, the present study aims at exploring, analyzing and classifying exaggeration characterizations in proverbs and sayings through analyzing the use of exaggeration expressions in English proverbs and sayings from a morphological perspective where the data analyzed are: (50) proverbs and sayings from the English language. Moreover, the current study is based on hypotheses revolve around the use of many exaggeration expressions in English and that are characterized by various and extensive morphological features. The study concludes that exaggeration expressions are highly and variously manifested in English proverbs and sayings through using various morphological techniques. Finally, the researcher has put forward a numbers of suggestions for further studies.

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: exaggeration, repetition, hyperbole, exaggeration function

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Artificial Intelligence (AI) scribes have revolutionized medical transcription, addressing challenges in clinical documentation by leveraging natural language processing (NLP) and speech recognition technologies. These systems alleviate administrative burdens on clinicians by automating transcription and integration into electronic health records (EHRs). This review explores state-of-the-art advancements in AI scribe technologies,their applications, and challenges, focusing on accuracy, efficiency, and privacy. By comparing methodologies and outcomes in recent studies, including Sporo AI and others, the paper highlights the transformative potential of AI scribes while underscoring the critical need for regulatory compliance, contextual understanding, and enhanced usability.

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Artificial Intelligence (AI) Scribes Medical Transcription Natural Language Processing (NLP) Speech Recognition Electronic Health Records (EHRs) Clinical Documentation Sporo AI GPT Models Healthcare Automation Transcription Accuracy Privacy and Compliance (HIPAA) Clinical Decision Support Telemedicine Voice Biomarkers Machine Learning (ML) Regulatory Considerations Medical Speech Recognition

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This paper provides an overview of the use of deep learning in plant protection, specifically in the identification of crop leaf diseases. Deep learning has gained significant attention due to its advantages in feature extraction and machine learning, making it a popular tool in various fields such as image and video processing, speech processing, and natural language processing. By applying deep learning to plant disease identification, it can provide more objective and efficient extraction of disease characteristics and improve research efficiency and technology transformation. our research aims to summarize recent advances in deep learning research related to crop leaf disease identification, highlighting current trends and challenges in this area, and serving as a useful resource for researchers studying plant pest detection. We are using CNN algorithm which provided 97% accuracy to detect disease.

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CNN, feature Extraction, plant leaf disease detection. Accuracy

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The Automobile Sector is a significant contributor of India's GDP and employment generation. Despite of various challenges such as soaring crude oil prices, shortage of semi conductor chip and supply chain disruptions, the Indian Automobile Market is currently the fourth-largest auto market globally and on its track to secure the 3rd position by 2026, signaling a promising future. The government is also highly supportive in terms of progressive policies and regulations. Today, India is considered as one of the key part of global strategy by global vehicle manufacturers and component suppliers. Even though India's Automobile Sector is immensely potential and growing at a rapid speed, it has to be mindful of challenges that are posed by the recent developments in the global market and adapt to the changing environment. This study provides insight on the recent trends that are shaping the global market and the challenges faced by the Indian automobile sector. The study also attempts to outline the key drivers that boost the growth and the opportunities that could exist for the major players of Indian Automobile Industry in future.

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GDP, Global Market, Automobile Sector, Employment

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Major General Alexander Cunningham, a British Army officer and pioneering archaeologist, is often regarded as the father of Indian archaeology for his monumental contributions in the 19th century. Cunningham's work fundamentally reshaped the understanding of India's ancient history, especially with his exploration and documentation of key archaeological sites associated with early Buddhism, Indianism, the Mauryan and Gupta periods. His contributions to Indian archaeology began in earnest with his appointment as the first Director-General of the Archaeological Survey of India (ASI) in 1861, where he laid the groundwork for systematic archaeological excavations across the subcontinent. One of Cunningham's most significant achievements was his identification and documentation of the ancient city of Taxila, a key center for Buddhism and early Indian civilization. His exploration of the ancient sites of Sarnath and Bodh Gaya, along with the discovery of inscriptions and monuments related to King Asoka, cemented his position as a trailblazer in the field. Cunningham's meticulous work on the Asokan Edicts, which he interpreted as crucial evidence of the Emperor's role in the spread of Buddhism, further deepened the understanding of India's ancient political and cultural evolution. Furthermore, Cunningham's contributions extended to the exploration of ancient Buddhist sites, including the identification of Tathagat Buddha's stupas and relics, shedding light on the historical and cultural relevance of the Buddha's life and teachings. His excavations and studies of the Gupta period's architectural marvels, including the temples at Deogarh, also revealed the rich heritage of India during a time of immense artistic and intellectual achievements. Despite facing challenges in the colonial context, Cunningham's work has left an indelible mark on the understanding of India's past, revealing hidden histories and connecting archaeological evidence to the cultural fabric of ancient India. His efforts have provided invaluable insights into the long-standing relationship between archaeology and the documentation of history, unearthing concealed evidence that continues to influence the study of Indian antiquities today.

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Alexander Cunningham, Indian archaeology, Archaeological Survey of India (ASI), Taxila, Sarnath, Bodh Gaya, Asoka,, Asokan Edicts, Tathagat Buddha, Gupta period, Indian history, Buddhist archaeology, Mauryan Empire, Ancient India, Ancient monuments, Inscriptions, Indian civilization, Deogarh temples, Excavations, Colonial archaeology.

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