https://semiengineering.com/driver-monitoring-raises-complexity-adds-privacy-concerns/ [semi_logo] Search for: [ ] [Search] Subscribe Zhong Wen English * Home * Systems & Design * Low Power - High Performance * Manufacturing, Packaging & Materials * Test, Measurement & Analytics * Auto, Security & Pervasive Computing * Special Reports * Business & Startups * Jobs * Knowledge Center * Technical Papers + Home'; + AI/ML/DL + Architectures + Automotive + Communication/Data Movement + Design & Verification + Lithography + Manufacturing + Materials + Memory + Optoelectronics / Photonics + Packaging + Power & Performance + Quantum + Security + Test & Analytics + Transistors + Z-End Applications * Events & Webinars + Events + Webinars * Videos & Research + Videos + Industry Research * Newsletters * MENU + Home + Special Reports + Systems & Design + Low Power-High Performance + Manufacturing, Packaging & Materials + Test, Measurement & Analytics + Auto, Security & Pervasive Computing + Knowledge Center + Videos + Startup Corner + Business & Startups + Jobs + Technical Papers + Events + Webinars + Industry Research + Special Reports Home > Auto, Security & Pervasive Computing > Driver Monitoring Raises Complexity, Adds Privacy Concerns Auto, Security & Pervasive Computing Driver Monitoring Raises Complexity, Adds Privacy Concerns Debate is just beginning about how in-vehicle data is collected, shared, and stored. September 1st, 2022 - By: Marie C. Baca popularity While you watch the road, your car may be watching you back. The automotive industry's transition toward self-driving technology means cars increasingly are equipped with features that measure driver alertness and engagement, among many other data points. Executives say such features save lives and spur innovation, while simultaneously raising significant technical, legal, and ethical questions. The discussion comes at a time when governments are exploring how driver monitoring systems can make roads safer. The European Union's new vehicle safety rules, which went into effect in July, require all new vehicles from July 2024 to be equipped with multiple features including systems that monitor driver drowsiness. Earlier this summer, the National Highway Traffic Safety Administration expanded its investigation into whether Tesla's Autopilot system exacerbates "human factors or behavioral safety risks by undermining effectiveness of the driver's supervision." The agency's initial investigation, opened last year, included an assessment of the "technologies and methods used to monitor, assist, and enforce the driver's engagement with the dynamic driving task during Autopilot operation." Experts agree that driver-monitoring systems are a critical bridge between today's high-tech autos and the fully self-driving cars of the future. Most commercial cars contain autonomous technology at a Level 2 or lower and require the driver to remain alert at all times. Only a few modern commercial vehicles have technology as high as Level 3, necessitating the driver to take control of the vehicle when it encounters a situation for which it is ill-equipped. Level 5 autonomous cars, which do not exist, require no human assistance. That means the cars of the foreseeable future will depend heavily on monitoring systems to ensure the driver remains alert and ready to operate the vehicle when necessary. The financial considerations for automotive OEMs go beyond liability to safety-related lawsuits and regulatory actions. Modern monitoring systems generate a massive amount of data, some of which is used by car companies to improve and progress autonomous technology. But the extent to which drivers are aware of this usage and are willing to swap their privacy for the promise of safer roads remains to be seen. National conversations about these topics are in their early stages, but some of the hardware involved, like pressure sensors and cameras, is well-established. Sensors in seats determine when and if airbags should deploy, while those in steering wheels measure whether or not the driver is "hands-on." Driver-facing cameras are included in most new cars today that sell for more than $40,000 or so, though the sophistication varies widely between auto models and makers. LEDs illuminate the driver's face and allow for the camera system to make its measurements. The cameras that monitor driver fatigue generally do so by measuring eyelid droop, alerting the driver to pull over if the system detects eyelid droop beyond normal levels. Far more complex is the hardware that enables artificial intelligence to process these relatively straightforward inputs and allow the car to make decisions based on that data. "As soon as you have an AI, then we need to talk about different levels of compute complexity," said David Fritz, vice president of hybrid-physical and virtual systems at Siemens Digital Industries Software. "A simple monitor is probably a 32-bit microcontroller doing some simple things. With AI, it can take six or eight cores, and it's got an AI accelerator unit (also called NSP or NPU). You need all that to recognize what you're seeing and make some intelligent decisions based on the context of what you're seeing. The compute that's required to do that is pretty significant." Vasanth Waran, senior director of business development for automotive at Synopsys, says automotive companies think about the technology in terms of driver monitoring systems, or DMS, and occupant monitoring systems, OMS. While a DMS is focused solely on the person operating the car, an OMS could be used to monitor distracting activity from other passengers or whether a baby is left in a car alone. Waran says it will take several years for the industry to figure out the standards that will allow for transmitting driver monitoring data beyond the vehicle. "It's not just vehicle-to-vehicle," he said. "It's also through the infrastructure. Then it doesn't have to go through a network if it can be transmitted back and forth through infrastructure. Another possibility is satellite communication. The standards are evolving to address a situation where you don't have infrastructure or connection to a 5G network, but you will still have communication." Driver monitoring data likely will be stored both in the cloud and locally to accommodate situations where the car is unable to connect to a network. "The first level of storage will always be some sort of local drive, whether it's a flash drive or a system with some sort of embedded storage, like a solid state drive," he said. "And once you park your car, you have the last 10 minutes of data going back to the cloud." Also required is lightning-fast communication between the monitoring systems, the driver, the systems with the car, other cars, and the manufacturer's computing infrastructure. Amol Borkar, director of product management, marketing and business development for Tensilica Vision and AI DSPs at Cadence, says the evolution is similar to what was seen with the internet over the past 20 years. "Initially, everything was local on our personal machines, but now we are always connected through our machines and phones," Borkar said. "At the moment, this data is mostly local for vehicles, as well. For the small percentage of vehicles that have built-in 3G (or higher) data communicators, it can be streamed out and used to improve the software, ADAS applications, and much more." [drivermonitor][drivermonitor] Fig. 1: An overview of processing between sensors and a central compute unit in an automotive. Source: Cadence Some critical tasks are likely to remain local due to uncertainties in network latency and performance. "As this segment evolves, V2X will also evolve significantly, allowing for much more dense communication and more connected vehicles," Borkar said. "The main motivations for V2X are currently road safety, traffic efficiency and energy savings, amongst others. As you can expect, there will be multiple building blocks, but many will revolve around high-speed communication (WiFi, cellular, automotive Ethernet), sensor and AI processing for analytics and understanding of audio, vision, lidar etc., and a central gateway or vehicle controller to manage all this data. All of this combined results in vehicles that could communicate with each other or the infrastructure to avoid accidents, reroute to reduce congestion in areas, and have a more deterministic flow of traffic." Additional complexity is found in the processes, both established and not yet invented, through which the car will use monitoring data to train an AI. "There are so many different possibilities, even when it comes to just watching your eyes," said Paul Graykowski, senior technical marketing manager at Arteris IP. "What if you are wearing sunglasses or a hat? Or encounter a road sign you've never seen before? You're going to need some kind of pathway to go up to the cloud and back from the cloud with the unique data sets that have been encountered. Your local SoC is processing all this and has to decide what's unique and interesting." So, too, are the implications of that decision-making. Gaize is a Montana-based company behind a product that measures and records eye movements, mimicking the eye-tracking test law enforcement uses to gauge driver impairment. AI-powered software then takes those inputs and correlates them to data sets of sober and impaired eyeballs. The software is focused on cannabis-related driver impairment, though Gaize CEO Ken Fichtler says that scope could broaden in the future. He says integrating the technology, or something similar to it, directly into a vehicle is part of the company's long-term roadmap. "The tests we use are the most studied out there for eye movement and impairment," said Fichtler. "We believe we're going to be able to use these tests and the data we capture to ultimately design a sort of continuous monitoring system, similar to the fatigue monitoring systems that exist today." The product in its current form consists of a virtual reality headset manufactured by Pico, which captures video of the eye movements and generates several types of data. The chip is from Qualcomm and the eye-tracking sensors are by Tobii. Law enforcement places the headset on the driver and the device runs through multiple tests. The first test measures the extent to which both eyes track a stimulus equally. Then the driver is asked to look toward the periphery of their vision on a horizontal plane to detect any "pronounced twitching" of the eye. A similar test detects twitching as the eye travels from a horizontal plane to 45 degrees, while another measures the ability of the eyes to smoothly track a stimulus without jerking. Other tests monitor vertical twitching of the eye, whether the eyes can cross and maintain focus, and how the pupil dilates and constricts in response to light stimulus. The data is stored on the device and also uploaded to the cloud. "Vector data, eye data, accelerometer and gyroscope data are all recorded at 90 times a second," said Fichtler. "It's very high resolution. Using that, we can then get a very clear understanding of what's happening in the eye and, by extension, what's happening in the body." Fichtler says the process is aimed at eliminating human error from sobriety field tests. "It's a great benefit not only to law enforcement as they go to prosecute these cases, but also the people being accused of these crimes," he said. "No one wants an officer that has a bias going into it or didn't perform the test properly or something like that. But these things happen." If technology like Gaize's is one day integrated into commercial vehicles, it will provide a new avenue for keeping impaired drivers off the roads. It also will generate concerns about how eye movement data is stored and shared, and the circumstances under which it can be accessed by law enforcement and other parties. Such issues speak to a legal and philosophical question that arises as driver monitoring technology becomes more sophisticated -- to what extent is one's car a private place? The answer, according to Paul Karazuba, vice president of marketing at Expedera, depends to some extent on who is asking and where that person lives. "A car is obviously a private place in the sense that strangers are not allowed to be in it, but a car is also a giant glass-encased cabin where you can look in and see what's happening," said Karazuba. "In Europe, car manufacturers have pretty much determined that the inside of your car is a private place. I don't know if that's necessarily true of the rest of the world." He noted that auto OEMs are likely to err on the side of keeping monitoring data more private rather than less, but legal precedents set in the U.S. and other major markets will be the deciding factor. A corollary issue is how the data generated from driver-monitoring systems will be used by insurers. Present-day owners of cars with self-driving features tend to have higher insurance premiums because high-tech cars are more expensive than their counterparts. That could soon change as countries seek to reduce driver error-related road deaths. Last month, the British government said manufacturers, not drivers, will be held liable for incidents that take place when a vehicle is controlling itself. Karazuba says he wonders about what will happen when driver monitoring systems allow a manufacturer to "know" when a particular driver is consistently distracted or making poor decisions. "Would a car manufacturer send a message to that person's insurance company saying, 'This person is a potentially dangerous driver'?" said Karazuba. "What's the ethical obligation of the car company to notify someone about that?" As recent Tesla headlines have shown, much of the public discussion as of late has been focused on the extent to which drivers fully understand what their car is and is not capable of, and the extent to which monitoring systems can ensure the driver is engaged with the car when necessary. Expedera's Karazuba says the process is essentially about education. "It's not about teaching people new skills, it's about telling them, 'Sit back and enjoy the ride, but at the same time, be ready to take over,'" he said. Ultimately, Siemens' Fritz says it will be critical for the AI to understand to only what it is encountering as it monitors a driver, but also the meaning of that data, which could vary from driver to driver. An experienced driver, for example, may not make the same facial expressions as a less experienced driver when encountering a challenging situation, because the experienced driver is more confident in their ability to drive appropriately. Sorting that out will require at least some amount of in-vehicle learning, he says, to allow the AI to understand the driver's idiosyncrasies and process them without latency or network connection issues. "A lot of people are going to try to do it in the cloud only to find that the cloud is cluttered with other things like pictures of people's breakfast," said Fritz. Related Privacy Protection A Must For Driver Monitoring Why driver data collected by in-cabin monitoring systems must be included as part of the overall security system. Big Changes Ahead For Inside Auto Cabins New electronics to monitor driver awareness, reduce road noise, ensure no babies or pets are left in hot cars. Automotive Bandwidth Issues Grow As Data Skyrockets Increasing autonomy and features require much more data to be processed more quickly. New Challenges For Connected Vehicles Security, safety and functionality concerns are dominating new automotive designs. Tags: Arteris IP autonomous driving autonomous vehicles Cadence DMS driver monitoring European Union Expedera Gaize Mentor National Highway Traffic Safety Administration Pico Qualcomm Siemens EDA Synopsys Tesla Tobii Marie C. Baca (all posts) Marie C. Baca is a technology editor at Semiconductor Engineering. Leave a Reply Cancel reply [ ] [ ] [ ] [ ] [ ] [ ] [ ] Comment * [ ] Name*[ ] (Note: This name will be displayed publicly) Email*[ ] (This will not be displayed publicly) [Post Comment] [ ] [ ] [ ] [ ] [ ] [ ] [ ] D[ ] Knowledge Centers Blogs Automotive Published on July 25, 2017 Technical Papers * Overview of Hardware-In-The-Loop (HIL) Simulations September 2, 2022 by Technical Paper Link * Artificial Neural Network (ANN)-Based Model To Evaluate The Characteristics of A Nanosheet FET (NSFET) September 2, 2022 by Technical Paper Link * Algorithm HW Framework That Minimizes Accuracy Degradation, Data Movement, And Energy Consumption Of DNN Accelerators (Georgia Tech) August 31, 2022 by Technical Paper Link * Designing for FPGA Accelerators August 31, 2022 by Technical Paper Link * Synergies And Limitations Between Road Infrastructure And Automated Driving August 31, 2022 by Technical Paper Link Trending Articles Big Changes In Architectures, Transistors, Materials Who's doing what in next-gen chips, and when they expect to do it. by Ed Sperling Fan-Out Packaging Gets Competitive Manufacturability reaches sufficient level to compete with flip-chip BGA and 2.5D. by Karen Heyman and Laura Peters Chip Backdoors: Assessing the Threat Steps are being taken to minimize problems, but they will take years to implement. by Jeff Goldman The Next Incarnation Of EDA Is there about to be a major disruption in the EDA industry, coupled to the emerging era of domain specific architectures? Academia certainly thinks so. by Brian Bailey Cryogenic CMOS Becomes Cool But that doesn't mean it's going to be mainstream anytime soon. by Brian Bailey Knowledge Centers Entities, people and technologies explored Learn More Related Articles DRAM Thermal Issues Reach Crisis Point Increased transistor density and utilization are creating memory performance issues. by Karen Heyman Wafer Shortage Improvement In Sight For 300mm, But Not 200mm Suppliers are investing new 300mm capacity, but it's probably not enough. And despite burgeoning 200mm demand, only Okmetic and new players in China are adding capacity. by Adele Hars Can Analog Make A Comeback? The industry reached an inflection point where analog is getting a fresh look, but digital will not cede ground readily. by Brian Bailey Big Changes In Architectures, Transistors, Materials Who's doing what in next-gen chips, and when they expect to do it. by Ed Sperling The Race To Zero Defects In Auto ICs 100% inspection, more data, and traceability will reduce assembly defects plaguing automotive customer returns. by Anne Meixner Keeping IC Packages Cool Engineers are finding ways to effectively thermally dissipate heat from complex modules. by Laura Peters and Karen Heyman Fan-Out Packaging Gets Competitive Manufacturability reaches sufficient level to compete with flip-chip BGA and 2.5D. by Karen Heyman and Laura Peters Chip Backdoors: Assessing the Threat Steps are being taken to minimize problems, but they will take years to implement. by Jeff Goldman * Sponsors [se_sp_ramb] [se_sp_syno] [Siemens-Lo] [se_sp_cade] [se_sp_flex] [c_01] [arteris-lo] [Infineon] [Riscure_l] * [INS::INS] Advertise with us * [INS::INS] Advertise with us * [INS::INS] Advertise with us * Newsletter Signup Popular Tags 2.5D 5G 7nm AI ANSYS Apple Applied Materials ARM Atrenta automotive business Cadence EDA eSilicon EUV finFETs GlobalFoundries Google IBM IMEC Intel IoT IP Lam Research machine learning memory Mentor Mentor Graphics Moore's Law Nvidia NXP OneSpin Solutions Qualcomm Rambus Samsung security SEMI Siemens Siemens EDA software Sonics Synopsys TSMC UMC verification Recent Comments * Lewis Sternberg on ML And UVM Share Same Flaws * Roger Stierman on L5 Adoption Hinges on 5G/6G * Marcel on MicroLEDs Move Toward Commercialization * Ragu Athreya on Is There A Limit To The Number of Layers In 3D-NAND? * Brian Bailey on AI Power Consumption Exploding * David S on AI Power Consumption Exploding * Mike Cormack on Cryogenic CMOS Becomes Cool * Lance Harvie on New Uses For AI In Chips * Doc R on Electronics And Its Role In Climate Change * Magdy Abadir on Is Standardization Required For Security? * guest on How Overlay Keeps Pace With EUV Patterning * Santosh Kurinec on Week In Review, Manufacturing, Test * sravani on Timing Library LVF Validation For Production Design Flows * Dr. F on A Sputnik Moment For Chips * Gary Dagastine on A Sputnik Moment For Chips * Mike Sottak on A Sputnik Moment For Chips * Robert Pearson on A Sputnik Moment For Chips * Raye E. Ward on A Sputnik Moment For Chips * Michael Williams on A Look Inside RF Design * SURESHBABU CHILUGODU on Week In Review: Manufacturing, Test * JC Bouzigues, Menta on Customizing Processors * Steve Swendrowski on IC Package Illustrations, From 2D To 3D * EMV on Hybrid Bonding Moves Into The Fast Lane * Dr. Appo van der Wiel on Variation Making Trouble In Advanced Packages * wang yu on Verification Of Functional Safety * Frederick Chen on High-NA EUV May Be Closer Than It Appears * Fact Cheq on The Week In Review: Design * Shiwen Huang on E-beam's Role Grows For Detecting IC Defects * Adele Hars on Wafer Shortage Improvement In Sight For 300mm, But Not 200mm * David A. Humphreys on IMS2022 Booth Tour: EDA And Measurement Science Converge * Merritt on Can Analog Make A Comeback? * subra ganesan on Meeting Processor Performance And Safety Requirements For New ADAS & Autonomous Vehicle Systems * George on Building A More Secure SoC * Amit Garg on A New Breed Of EDA Required * Karl Stevens on A Minimal RISC-V * Karl Stevens on EDA Gaps At The Leading Edge * Micah Forstein MS. on Risks Rise As Robotic Surgery Goes Mainstream * Dr. Punam Raskar on Who Does Processor Validation? * Dr. Dev Gupta on Variation Making Trouble In Advanced Packages * Cox on DRAM Thermal Issues Reach Crisis Point * David Leary on DRAM Thermal Issues Reach Crisis Point * Geeeeeee on DRAM Thermal Issues Reach Crisis Point * Pedro Ferro Laks on SOT-MRAM To Challenge SRAM * Obviously silly on DRAM Thermal Issues Reach Crisis Point * Simon on DRAM Thermal Issues Reach Crisis Point * Gareth on Energy Harvesting Starting To Gain Traction * SriniB on Can Analog Make A Comeback? * Kevin Cameron on Can Analog Make A Comeback? * Jacques Baudier on Are Tiny MicroLEDs The Next Big Thing For Displays? * Kamil Bro on Energy Harvesting Starting To Gain Traction * Sumit on Four Steps To ISO 26262 Safety Mechanism Insertion And Validation * What Does The Antitrust Law Do For Baseball? on Power Aware Intent And Structural Verification Of Low-Power Designs * Santosh Kurinec on Will Big Competition Attract More Talent For IC Companies? * Dean Freeman on Wafer Shortage Improvement In Sight For 300mm, But Not 200mm * Balvinder Singh on The Challenge Of Optimizing Chip Architectures For Workloads * Katherine Derbyshire on Hiding Security Keys Using ReRAM PUFs * Florian on Big Changes In Materials And Processes For IC Manufacturing * Ron Lavallee on The Challenges Of Incremental Verification * Laura Peters on Big Changes In Materials And Processes For IC Manufacturing * Chris Ethen on Big Changes In Materials And Processes For IC Manufacturing * David on Seven Hardware Advances We Need to Enable The AI Revolution * brad jackson on Paving The Way To Chiplets * Riko Radojcic on Paving The Way To Chiplets * Andrew Nambudripad on Open-Source Hardware Momentum Builds * Steve on Energy Harvesting Starting To Gain Traction * WEC on Hiding Security Keys Using ReRAM PUFs * Chris Riches on Photomask Shortages Grow At Mature Nodes * Marcos Tadeu Scaff on Zonal Architectures Play Key Role In Vehicle Security * Ken Rygler on Photomask Shortages Grow At Mature Nodes * reyhan on A Novel Power-Saving Reversing Camera System with Artificial Intelligence Object Detection * S Pietri on Energy Harvesting Starting To Gain Traction * David Joshua Plager, AIA, NCARB on Breaking The 2nm Barrier * Andy on Verifying Side-Channel Security Pre-Silicon * Ron Lavallee on Architecting Faster Computers * 2cents on Architecting Faster Computers * Ron on Architecting Faster Computers * Scott on UCIe: Marketing Ruins It Again * Ami Vider on Open-Source Hardware Momentum Builds * Kevin Murphy on Slowdown, But No Correction * paul adriaan kleimeer on Chasing After Carbon Nanotube FETs * paul adriaan kleimeer on Why Comparing Processors Is So Difficult * paul adriaan kleimeer on Will Steering Wheels Ever Disappear? * belal on Is DVFS Worth The Effort? * Allan Cantle on CXL and OMI: Competing or Complementary? * Mike Rodgers on Why Comparing Processors Is So Difficult * Ross R. Youngblood on A Brief History of Test * Phil Hollis on What Causes Semiconductor Aging? * Fumi on 2D Semiconductors Make Progress, But Slowly * Kursad Albayraktaroglu on Why RISC-V Is Succeeding * Dr. Dev Gupta on Fundamental Shifts In IC Manufacturing Processes * BIll M on Fundamental Shifts In IC Manufacturing Processes * davidgmillsatty on Constraints On The Electricity Grid * Steve on Constraints On The Electricity Grid * william (Bill) J Atkinson on Technical Papers: Organized, Timely, And Relevant * Andy deng on Why Banks Should Be More Worried About Security * Prince J on Understanding Memory * Efi Rotem on Challenges Grow For Finding Chip Defects * Kevin Cameron on Which Processor Is Best? * SAmer Diab on A Breakthrough In Silicon Bring-Up * Apoorva on Securing Automotive Over-The-Air (SOTA) Updates * Brian Bailey on Why RISC-V Is Succeeding * Jason on Test Engineers In Very Short Supply * s nedunuri on Will Steering Wheels Ever Disappear? * Rupert Baines on Which Processor Is Best? * Lawrence on Why RISC-V Is Succeeding * dev dutt on 2D Semiconductors Make Progress, But Slowly * solidproes on How To Solve Automotive Electrical Design Challenges To Get To Market Faster * Paul Lue on Why RISC-V Is Succeeding * Siddhartha Nath on Does EDA Sell Fear? * Dean Freed on Does EDA Sell Fear? * Harry Chen on Does EDA Sell Fear? * Edgar Ancker on Why 450mm wafers? * Dale on Automotive Functional Safety Compliance In EDA Tools And IP * Kvs on Why RISC-V Is Succeeding * Rajeev Vadjikar on Transistors Reach Tipping Point At 3nm * Mark LaPedus on Next-Gen 3D Chip/Packaging Race Begins * Arnaud PHELIPOT on What Causes Semiconductor Aging? * Tanj Bennett on Thermal Management Implications For Heterogeneous Integrated Packaging * Mark LaPedus on Technology Advances, Shortages Seen For Wire Bonders * Jan Hoppe on What Causes Semiconductor Aging? Overview of Hardware-In-The-Loop... Technical Paper Link Artificial Neural Network (ANN)-... Technical Paper Link [se_logo_bl] About * About us * Contact us * Advertising on SemiEng * Newsletter SignUp Navigation * Homepage * Special Reports * Systems & Design * Low Power-High Perf * Manufacturing, Packaging & Materials * Test, Measurement & Analytics * Auto, Security & Pervasive Computing * Videos * Jobs * Technical Papers * Events * Webinars * Knowledge Centers * Industry Research * Business & Startups * Newsletters Connect With Us * Facebook * Twitter @semiEngineering * LinkedIn * YouTube Copyright (c)2013-2022 SMG | Terms of Service | Privacy Policy This site uses cookies. By continuing to use our website, you consent to our Cookies Policy ACCEPT Manage consent Close Privacy Overview This website uses cookies to improve your experience while you navigate through the website. The cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. We do not sell any personal information. By continuing to use our website, you consent to our Privacy Policy. If you access other websites using the links provided, please be aware they may have their own privacy policies, and we do not accept any responsibility or liability for these policies or for any personal data which may be collected through these sites. Please check these policies before you submit any personal information to these sites. Necessary [*] Necessary Always Enabled Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information. Non-necessary [*] Non-necessary Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website. SAVE & ACCEPT Quantcast