Protecting brand reputation with AI

Protecting brand reputation with AI

  04:27    Silver Push

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We just learned something quite distressing – that one in 10 videos out in the online jungle we call the internet – can contain something potentially ‘harmful’ and ‘damaging’.

What we mean by this is that some videos contain certain elements that may not be accurately reflected by the title or tags associated with it. This poses a problem for brands who may not want to be associated with adult themes or extreme violence.

To find out what this means for brands and what options they have, we spoke to Kartik Mehta, Chief Revenue Officer, SilverPush. With their new product Mirrors Safe, the brand offers an AI-Powered context-relevant brand suitability platform to help prevent unwanted associations.

In order to build this product and understand they extent of the issue, Silverpush reviewed 15 million videos across the largest video hosting and sharing platforms in the SEA region using Mirrors Safe. With one in 10 or 10% containing images or negative associations (according to Silverpush criteria), there is definitely a need for a solution.

Congrats on the launch of Mirrors Safe. How do you see this new product helping brands and their advertisements?

Brands today are faced with different types of risks – financial risks, legal risks, and I guess the most important part of it is the reputation risk which could have larger concerns and probably a long-lasting impact on the overall brand equity. The existing brand safety measures like blocklists and whitelists are primarily focused on the principle of exclusion, which does protect brands to an extent but can also lead to one of the most pressing brand safety related concerns of over-blocking. Which can lead to brands missing the opportunity of engaging with the audiences across the right kind of content. 

Whereas Mirrors Safe’s computer vision powered in-video context detection identifies faces, actions, scenes, emotions, on-screen-text in a streaming video to detect content that features violence, smoking, nudity, arms & guns and more. It detects these contexts only when they feature in a video, and not just by relying on keywords used to describe the video – which often times are misleading and can result both in unsafe placements as well as over blocking. 

For instance, a video featuring smoking or violence might not be described so in its title, description or meta tags. There is no way for keyword-based solutions to identify these damaging contexts to filter out this video. Which can lead to household brands advertising across content which is highly unsuitable for their brand image. On the other hand, keywords like shoot, kill, crash, and even gun (some of the most blocked keywords) can easily be used within perfectly safe contexts, (like movies and songs). 

Moreover, Mirrors Safe’s context detection makes it possible to offer brand suitability that can be customized for each brand or each category without following the blanket exclusion principles. 

According to your research, 1 in 10 videos are deemed to be associated with dangerous or damaging content. How were you able to analyze around 15 million videos to generate this data?

Silverpush churned approximately 15 million videos across the largest video hosting and sharing platforms in the SEA region using Mirrors Safe. We used a randomly chosen inventory across platforms from our existing database – previously used to run campaigns using our video advertising platform Mirrors.  

It was found that nearly 8-9% of analyzed content to be deemed brand unsafe. This means these videos featured one or more unsafe contexts like nudity, smoking, violence, arms and guns, and more. 

However, a bigger discovery was the difference between the results found by exclusion through traditional methods like keyword lists vs. Mirror Safe’s in-video context detection technology.

For instance, when we used both methods to identify unsafe videos for one of the top brand unsafe categories – nudity and adult content, Mirrors Safe (through its frame-by-frame parsing) identified 300% more video content featuring unsafe context in this category, compared to exclusion through keyword lists.

A single damaging ad placement can harm brand perception in the consumer’s mind. This discovery highlights the potential harm that existing traditional measures are unable to detect. This has been witnessed time and time again, with some of the largest video advertising platforms being unable to keep brands safe from damaging content.

Have you been able to measure or estimate the negative impact of these associations for the brand? 

There is already a plethora of information available on how even a single ad placement across harmful content can irreparably damage brand perception for a long time in the consumers mind. A 2019 study Trustworthy Accountability Group & Brand Safety Institute found that 80% consumers will stop or reduce buying products advertised against extreme or violent content. And, 70% believe advertiser and the agency are most responsible for a brand’s ad placements.

With our platform Mirrors, we have been serving contextually targeted video advertising across platforms since 2018. And we identified the challenge posed by traditional brand safety measures while serving our clients. We realized that ensuring brand safety is even more of a challenge across video formats, as NLP based technologies that work for other formats are ineffective in gauging the right context featured in video content. 

Conversations and feedback from partners first led us to introduce a safety feature in Mirrors, where brands working with us did not report a single unsafe exposure since the launch of the feature. This further led us to launch Mirrors Safe, which can be deployed as a standalone context relevant suitability platform. 

How has this solution helped brands so far? Do you have any initial test cases or beta usage that you can share?

I will start with the most interesting use case, that is highly relevant today.  

Helped brands navigate the extreme over-blocking of COVID-19 related content 

As brands and platforms rapidly add terms associated with COVID-19 to their keyword block, Coronavirus has become one of the most blocked keywords today. We have found advertisers looking to avoid unsafe brand exposure around this sensitive topic are forced to exclude news entirely from their list of targeted channels and publishers. However, excluding news and related channels entirely from advertising strategies across platforms is killing reach for brands. 

One of the key factors behind extreme COVID-19 related over-blocking is the inability to detect if the COVID-19 related stories are informative Vs. stories that can harm brands – leading to blanket exclusions. Mirrors Safe identified what the video content features to differentiate the stories, in the following ways: 

• On-screen text recognition: Mirrors Safe identifies and filters out videos that have related text written on the screen (e.g. Coronavirus or COVID-19). And can help differentiate between morbidity related stories Vs. more positive stories around for instance precautions. 
• Object and action detection: the system can identify objects like masks, stretchers, and actions like coughing and sneezing and understand the concentration of this content within a single video through frame by frame parsing.
• Faces: with this outbreak certain public figures are also on brands’ blocklists (yes, Trump). In-video context detection can accurately identify faces to filter out related content.

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Moving from Video Interruption to Integration Through Contextual Advertising

Moving from Video Interruption to Integration Through Contextual Advertising

  00:32    Silver Push

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Moving from Video Interruption to Integration Through Contextual Advertising

Video advertising has become a highly effective tool for brands and marketers to communicate their messages to online audiences. In the year 2018, $10.228bn were spent in digital video advertising in the United States alone.

Since its inception, video advertising has faced the criticism of being inherently interruptive in nature. Online users tend to skip or ignore ads that appear to them as annoying or interruptive. This non-engagement of users with the ads is a serious headache for marketers, and they are struggling to find the way out.        

Research shows that brands are now increasingly concerned about the interruptive user experience when running their video advertising campaigns. For brands, user experience has become a significant factor to consider while devising their video advertising strategy. Brands are trying to make in-video ads more engaging and less annoying for users. In order to draw effective user engagement, ads should be able to capture the user attention in the first few seconds.

Video ad formats also play an important role in driving better user experience and engagement. By deploying better formats, marketers can make their advertising strategy more effective. According to eMarketer, sixty percent of video ads fall in the in-stream category. Majority of the marketers are currently deploying interruptive in-stream ad formats that can be easily skipped or ignored. Pre-roll and post-roll are used more often over other formats such as overlay video and mid-roll. Overlay ad format, which places an ad over the video content, offers an advantage over other in-stream formats of not overtly interrupting the underlying video content being watched by the user. Thus, overlay ads are less annoying and tend to provide better user experience.

Mid-roll format is least favored by the marketers, especially for short video content, because it is highly interruptive. Therefore, marketers are currently mainly utilizing pre- and post-roll in-stream ad formats for achieving their advertising goals and the whole video content itself is being left uncapitalized. Here, the overlay format comes to rescue. It allows marketers to capitalize on the unutilized video content without being interruptive to users.  

Brands have identified certain obstacles in the path of video ad innovation. These include inadequate budget, lack of in-house expertise, misaligned in-house teams, lack of agency relationship, and lack of strong external technology partnership. To achieve their video advertising goals, brands and marketers should focus on innovative, non-interrupting ad formats. But only using the right in-video ad format will not work, marketers should make use of robust, efficient and effective advertising technology such as AI advertising, and give utter importance to context. They should serve contextually relevant in-video ads that are well-aligned with the content the user is consuming.

According to the industry experts, video advertising strategy in the future will be impacted by factors such as demand for non-interruptive ads, growth of over-the-top and connected TV ad formats, growth of social networking and video sharing advertising formats, and demand for contextual advertising.

Users’ demand for non-interruptive ads on connected TV has grown over the years in sync with the growth in its viewership. Currently, in-stream video advertising on this platform is largely interruptive in nature. Contextual video advertising offers an effective solution to marketers to mitigate this interruption on connected TV and enhance user experience. 

By using the right mix of in-video ad formats and contextually aligned ads, advertisers can turn upside down the user experience from being interruptive to engaging. To display contextually aligned video ads, a highly effective solution is afforded by AI powered in-video context detection technology.

However, AI-powered solutions that are dependent on machine learning, NLP and semantic analysis, miss the mark when it comes to understanding the sub-text, nuanced contexts and complex relationships words have in written or spoken language.   

Computer vision powered contextual advertising technology provides very high degree of context relevance. This technology works by accurately detecting contexts in video such as faces, emotions, logos, objects, scenes and activities in order to display in-video ads that are in line with what the user is actively engaging with. Highly contextually relevant ads appear non-interruptive and appealing to users, and boost the chances of users watching or clicking them.     

With AI-powered contextual video advertising, marketers can seamlessly integrate ads with the video content the user is watching, thereby providing a non-interruptive, highly engaging user experience.      

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Choosing Between Contextual Advertising and Audience Targeting – Which is Better?

Choosing Between Contextual Advertising and Audience Targeting – Which is Better?

  01:02    Silver Push

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Choosing Between Contextual Advertising and Audience Targeting – Which is Better?

For marketers, choosing contextual advertising over audience targeting or vice versa has always been dilemmatic. Contextual advertising involves placement of ads on the basis of the content the user is engaging with, whereas audience targeting involves use of cookies to track users and display ads. Here, we will try to provide a solution to this dilemma. We will consider the data available from different studies and draw a conclusion.

Balancing audience and context is difficult for the majority of marketers, shows a survey conducted by Sizmek. The solution to this problem is not just as simple as targeting both audience and context, as for 8 in 10 of the survey participants, targeting both has a negative impact on the advertising campaign.

90% of the participants said that they expect to increase the scale of their contextual targeting and find new audiences. 80% said that in the coming year, it will be either a critical or high priority for them to achieve both audience and contextual targeting at scale.

For the direct response campaigns, 42% of the participants said that their targeting strategy involves only audience or gives more importance to audience over context, while 37% said audience and context are equally important. 21% said that their targeting strategy involves only context or gives more importance to context over audience.

For the brand campaigns, 37% of the participants said that their targeting strategy involves only audience or gives more importance to audience over context, while 35% said audience and context are equally important. 28% of the respondents said their targeting strategy involves only context or gives more importance to context over audience.

75% of the respondents agreed that deploying artificial intelligence in advertising increases the performance of the ad campaigns. 81% said that they plan to increase the use of artificial intelligence in advertising.

With the coming in effect of the data privacy regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), and the gradual phasing-out of third-party cookies in Chrome by Google, a major shift from cookie-based audience targeting to contextual advertising has begun.

77% of the survey’s participants anticipated that the GDPR and other privacy laws will make it harder for marketers to target audience through the means of third-party data. 80% of the respondents said they will improve their contextual targeting.

Industry experts think that AI-powered contextual advertising will become the preferred mode of online advertising as it does not rely on users’ data.

Another study published on The Drum compared contextual targeting to audience targeting in terms of attention, cost and brand lift. It found that the average time spent by individuals on ads in the case of contextual advertising was 12% greater than when audience targeting was used. On a CPM basis, audience targeting cost was found to be 4.7 times more expensive than contextual targeting. Apart from the data costs, the media costs incurred in the case of contextual targeting were 6.3% lesser than audience targeting.

Brand lift per second of attention was 2.1% in the case of audience targeting, while it was 3% for contextual targeting. At developing brand impact per second of attention, contextual targeting came out to be 43% more efficient than audience targeting. The study found that for every dollar spent, contextual targeting is 7.5 times more efficient than audience targeting in achieving brand lift.

From the above two studies, two conclusions can be drawn – firstly, contextual advertising is much more effective and efficient than audience targeting, and secondly, marketers are increasingly considering contextual targeting, especially AI-powered contextual advertising.

However, most of the AI powered solutions currently available in the market depend on the use of machine learning (ML), natural language processing (NLP) and semantic analysis. These solutions fail to truly understand the sub-text, nuanced contexts, and complex relationship words have in written or spoken language.  

AI-powered contextual advertising solutions that use computer vision are far more effective and accurate, offering a higher degree of context relevance that overcomes the limitations of traditional keyword targeting and NLP based technologies. Computer vision enables detection of contexts in video such as faces, emotions, logos, objects, scenes and activities with high accuracy, thus allowing advertisers to display in-video ads that are in line with what the user is actively engaging with. Computer vision powered contextual advertising allows brands to achieve unparalleled user engagement, reach and ROI.

The benefits offered by AI and computer vision powered contextual targeting are not limited to boosting performance of ad campaigns, but also include successful resolution of the grave problem of brand safety. Accurate detection of unsafe or inappropriate contexts in video enables marketers to effectively avoid any sort of undesired ad placement, thus ensuring brand safety.

For marketers seeking an advertising strategy that is compliant with privacy regulations, cookieless, highly effective and brand safe, AI and computer vision powered contextual advertising surpasses audience targeting.  

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Silverpush Launches Mirrors Safe, An AI-Powered Context-Relevant Brand Suitability Platform

Silverpush Launches Mirrors Safe, An AI-Powered Context-Relevant Brand Suitability Platform

  06:09    Silver Push

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Silverpush Launches Mirrors Safe, An AI-Powered Context-Relevant Brand Suitability Platform

Silverpush, a leading AI-powered technology solutions company, today announced the launch of their new brand suitability platform Mirrors Safe. This product forms a part of the company’s computer vision-enabled video intelligence product suite, which is transforming how some of the largest brands globally reach their most engaged audience in a brand-safe environment. 

Brands today face a significant financial risk from a potential crisis involving their advertising. A 2019 study by Trustworthy Accountability Group (TAG) and Brand Safety Institute (BSI) found that 80% of customers will stop or reduce buying products that place advertisements across harmful or offensive content, and around 70% blame the brand or the agency for such placement. This survey exhibits the real and measurable risk that a preventable brand safety crisis can pose. 

Through the use of AI-powered in-video context detection, Mirrors Safe transcends challenges of traditional brand safety measures like keyword-based technologies and whitelisted channels. Trained with millions of pieces of visual content, the platform identifies in-video contexts like objects, actions, faces, and scenes within a streaming video, and contextually filters out harmful content across an extensive set of brand unsafe categories including nudity, smoking, violence, crashes, and much more. 

Mirrors Safe’s advanced algorithm uses five parameters to calculate a comprehensive brand suitability score, that measures not only safety and suitability of content, but also of the page and the channel. These include: 

• Engagement: likes, dislikes & participation that the content generates. 
• Safety: exclusion through in-video context detection, on-screen text, and audio sentiment analysis. 
• Influence: organic influence that channel/page/content creates. 
• Relevance: how relevant is the content in terms of its peer channel/page category. 
• Momentum: consistency that channel/page maintains or grows in terms of engagement. 

Kartik Mehta, CRO at Silverpush said, “What sets Mirrors Safe apart is its ability to custom define the scope of harmful contexts that are unique to every brand. Thus, helping brands move beyond just brand safety to a truly brand-suitable environment. This is limited with existing keyword and natural language processing (NLP) based blanket exclusion technologies, as these often fail to understand the complex undertones and various contexts words can be used for”. 

In a testing phase, Silverpush analysed ~15 million videos across the largest video hosting and sharing platforms in South East Asia using Mirrors Safe. Overall, 8-9% of content was found to be brand unsafe across multiple categories, indicating that nearly 1 in every 9 video ad placements are placed around harmful and damaging content. Top unsafe content categories identified include smoking, violence, adult, and extremist content. 

To further showcase the impact context-relevant brand safety can bring in, the company used both traditional measures and Mirrors Safe’s in-video context detection to identify content for one of the top brand unsafe categories – nudity and adult content. Mirrors Safe, through its frame by frame parsing of video content, identified 300% more videos featuring in-video unsafe contexts in this category, compared to traditional methods. 

Even a single misplaced ad can harm brand perception for a long time in the consumer’s mind– this discovery points out the inefficacy and potential harm that existing measures can have, which has been witnessed time and again from continued failures of some of the largest video advertising platforms in keeping brands safe. 

Kartik further added, “Mirrors Safe further addresses one of the most pressing brand safety challenges of content over-blocking – a result of blanket exclusion measures offered today. This significantly limits campaign performance and often forces marketers to switch off controls in favour of reach. Mirrors Safe’s in-video context detection technology prevents over-blocking and only filters videos that actually feature unsafe contexts, ensuring brand safety without hampering monetisation and performance.”

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Silverpush Launches AI-Powered Brand Suitability Platform – Mirrors Safe

Silverpush Launches AI-Powered Brand Suitability Platform – Mirrors Safe

  04:48    Silver Push

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Mirrors Safe uses computer vision to provide unequaled brand suitability for in-video ad placement.

Singapore, 20 May 2020: Silverpush has today announced the launch of its new AI-powered brand suitability platform – Mirrors Safe. Silverpush is well-acknowledged for its AI-powered contextual video advertising and real-time moment marketing products that enable brands to achieve unprecedented reach and user engagement.

Brand safety poses a serious risk to brands. Research shows that 80% of customers will not buy products at all or reduce their buying of products from brands that place ads across any type of harmful or offensive content. 70% of the customers hold the brand or agency for hurtful ad placement.

By using computer vision to detect contexts in video, Mirrors Safe overcomes the limitations of conventional brand safety methods such as keyword-based blacklists and whitelisted channels. It accurately detects contexts in videos such as faces, objects, logos, emotions, scenes and activities and filters out harmful content across a broad range of brand unsafe categories including terrorism, violence, nudity, hate speeches, smoking, etc.

Mirrors Safe makes use of an advanced algorithm for calculation of brand suitability score. This comprehensive score takes into account five parameters. This score measures safety and suitability of the content, page and channel. The five parameters are –

• Engagement: likes, dislikes & participation that the content generates
• Safety: exclusion through in-video context detection, on-screen text, and audio sentiment analysis
• Influence: organic influence that channel/page/content creates
• Relevance: how relevant is the content in terms of its peer channel/page category
• Momentum: consistency that channel/page maintains or grows in terms of engagement

Silverpush’s CRO, Kartik Mehta, said: “What sets Mirrors Safe apart is its ability to custom define the scope of harmful contexts, that are unique to every brand. Thus, helping brands move beyond just brand safety to a truly brand suitable environment. This is limited with existing keyword and natural language processing (NLP) based blanket exclusion technologies, as these often fail to understand the complex undertones and various contexts words can be used for”.

Silverpush used Mirrors Safe to analyze about 15 million videos across the largest video hosting and sharing platforms in the South East Asia region using Mirrors Safe. The analysis found 8% to 9% of the video content as brand unsafe, i.e roughly 1 in 10 videos has some type of brand damaging content.

Silverpush compared traditional brand safety measures with Mirrors Safe to identify nudity and adult contents in videos. Result was amazing as Mirrors Safe identified 300% more unsafe videos compared to conventional brand safety methods.

This finding brings into light the inefficacy of the traditional brand safety measures and the potential harm they can do to a brand’s image. The use of traditional measures has led to serious brand safety issues for some of the biggest video platforms.

“Mirrors Safe further addresses one of the most pressing brand safety challenges of content over-blocking – a result of blanket exclusion measures offered today. This significantly limits campaign performance and often forces marketers to switch off controls in favor of reach. Mirrors Safe’s in-video context detection technology prevents over-blocking and only filters videos that actually feature unsafe contexts, ensuring brand safety without hampering monetization and performance” – Mehta added.

Visit silverpush.co/mirrors-safe/ to know more about Mirrors Safe.

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  01:56    Silver Push

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How are brands responding to COVID-19? A brand marketer survey across SEA market

Brands have been profoundly affected by the coronavirus pandemic. Brands’ response to the coronavirus pandemic not only impacts consumers’ trust today, but it will also significantly impact future purchasing decisions. Moreover, brands could face irreparable damage to their reputation due to brand safety risks associated with COVID-19 related content.

To gain insight into how brands are responding to COVID-19 pandemic, Silverpush conducted a survey of 150+ agency heads, business leads in media, and brand marketers in the SEA region in April 2020.

The survey aimed to understand how brands are adapting their marketing strategies to the impact of the COVID-19 outbreak and how they are mitigating the very real brand safety risks the rapidly growing coronavirus related content consumption poses.

How are brands re-imaging and engaging consumers in light of the pandemic?

The survey found that in the light of the pandemic, brands are reimaging by adapting their marketing tone and initiatives to consumer expectations. Only 5% respondents reported no change in brand positioning pre and post COVID-19, whereas 95% reported a distinct shift that resonates with government policies, and responds to the new consumer expectation.

Ad spending poised to decline

The industries heavily impacted by coronavirus outbreak such as travel, hospitality, physical retail and more have and will continue to paused marketing initiatives. Only 16% respondents said these industries will protect marketing budgets for a stronger comeback later.

Moreover, the survey indicates that it is unlikely that the industries such as health and FMCG that are currently experiencing higher demand will increase marketing spend to capture the demand more aggressively. Even though past recessions have shown that aggressive cuts in ad spends can lead to longer recovery cycles.

Ad Spends are shifting to digital channels

Even with significantly increased TV viewership across SEA, boosted due to government-imposed lockdowns across the region, and various studies indicating curtailed TV ad spends can adversely affect brand health measures - only 2% respondents said brands are spending more on TV and mainstream media, and a large percentage indicated rapid shift to various digital channels.

Brand safety is a key concern, and is driving ad spend cuts

Industries, except few such as health, hygiene, pharma, etc., are stringently avoiding advertising across COVID-19 related content. Publisher news sites and news channels on platforms like YouTube are facing advertisers’ block-lists due to coronavirus-related coverage.

A measure of advertisers’ confidence on brand safety tools is depicted by how despite using third party tools to ensure safe ad placements, brands are reducing marketing budgets and pausing advertising specifically to avoid association with Coronavirus related content.

71% respondents reported brands are reducing marketing budgets ranging from complete halt of marketing spends leading to up-to 80% budget cuts, in order to avoid running ads across coronavirus related content

Can context relevance be the answer?  

Emerging AI powered solutions are increasingly focusing on providing context relevance, and are fast becoming an answer to brand safety woes. AI enables processing of large volumes of data at speed, with better context, at higher scale and improved targeting efficiencies.

However, most of these contextual targeting solutions still depend on the use of NLP and semantic analysis, not truly understanding the sub-text, nuanced contexts, and complex relationship words have in written or spoken language.

AI and computer vision-powered video advertising solutions can detect in-video contexts, offering a higher degree of context relevance that surpasses limitations of traditional keyword targeting and NLP based technologies. They offer unparalleled insight for advertisers to place context-relevant in video ads and exclude unsafe content in a highly structured manner, and at the scale programmatic has traditionally offered.

You can access the full report ‘Brand Response to COVID-19 in SEA’ for detailed insights from the survey. 

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  23:28    Silver Push

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Understanding the Post Covid-19 Contactless Workplaces

The coronavirus pandemic has changed many aspects of human lives. Many people are now working from home. The post Covid-19 workplaces will not be the same conventional workplaces that people have been familiar with for years. Workplace safety will take priority over other matters.

The workplaces will undergo a radical shift from touch-based to touchless. Things like fingerprint-based biometric devices, touch-based screens for booking conference and meeting rooms, kiosks for guest check-in, handle-operated doors, etc. will have to be replaced with viable alternatives to prevent the spread of infectious diseases and ensure employee safety.

The contactless workplaces will make use of automation and touchless technology. Normal doors will be replaced by automatic doors, elevators will be voice-controlled, lighting system will adjust brightness automatically according to the time of the day, temperature control system will be adjusted by gestures or voice, and water dispensers will automatically pour water on keeping a bottle or glass below the tap.

The washrooms will have touchless automatic faucets, hand-free soap dispensers, and automatic flush powered by infrared technology. These products will not only reduce spread of germs, but also save water and soap. Along with touchless hand dryer, touchless paper towel dispenser will also be provided.

The contactless workplaces will make use of contactless attendance system powered by facial recognition technology in place of fingerprint-based biometric attendance system. A computer vision powered face-recognition-based attendance system can easily recognize the faces of employees for the purpose of attendance. Computer vision is an advanced field of artificial intelligence that enables computers to see like human beings and easily identify visual content in images and videos.

Besides powering the face recognition biometric systems, computer vision powered solutions can help employers ensure wearing of face masks by employees and enforce workplace social distancing and sanitization compliance. This technology can also bring into notice if an employee coughs or sneezes.

As an employee health and safety measure, workplaces will have to make use of touchless temperature recording technology. This technology will work by using thermal sensors for recording temperature of both employees and visitors. If any anomaly is detected, it will be instantly reported to the concerned department.

Post Covid-19 workplaces will not allow sharing of accessories such as headphones and each employee will be provided individual accessories along with laptops or desktops. Professional cleaning and sanitization protocols will be regularly implemented for workstations, devices, conference and meeting rooms, reception area, cafes, etc. Easy access to hand sanitizers will be provided throughout the workplace for both employees and visitors. The sensor-based touchless garbage bins will provide a safe way to dispose of garbage.

Workplaces will incorporate antimicrobial materials into interior design elements such as wall paints, door sheets, window shades, etc. Such materials will resist the growth of microbes, thus providing a cleaner surface. To ensure workplace social distancing, workplaces will follow a de-clustering approach by keeping individual employee desks wide apart from each other. This can be achieved by using a larger office area or by creating branch offices. Encasing individual desks will provide added protection from transmission through respiratory droplets. Post Covid-19 workplaces will require advanced air filtration technology in order to effectively filter out disease causing microorganisms.

The post Covid-19 contactless workplaces, by making use of advanced technologies, will help employers to carry out their business, while ensuring employee health and safety.

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