The new 'MoodLight' knows how humans feel and is able to portray those emotions through beautiful, captivating colors. The lamp is actually connected to Twitter and sources the 700,000,000 Tweets that are posted each day, to represent the mood of the world based on what they are communicating through this platform.
The one-of-a-kind light is able to determine different emotions based on the words people use in their posts. The emotions displayed include love, joy, surprise, anger, sadness and fear and are distinguished by posts like "I miss him" or "I love you."
What is most interesting about this lamp is that you can customize the lighting configurations to represent more than just the news from Twitter. Different combinations can be used -- such as two flashes of red -- to indicate that you have a new Gmail message.
The 'MoodLight' is currently working towards its goal on Kickstarter.
Emotion-Powered Lamps
'MoodLight' Emits Twirls of Color Based on the Emotions of the World
Trend Themes
1. Emotive AI - Developing AI algorithms to detect emotions and reactions of individuals in real-time can be leveraged across industries to enhance customer experience and personalize services.
2. Data-driven Design - Leverage data to enhance personalization in design, from embracing a more empathetic user experience to creating products that adjust to changing environmental conditions.
3. Social Media Analytics - With advancements in AI and machine learning, companies can leverage social media data to monitor customer conversations, predict sentiment, and make data-driven business decisions.
Industry Implications
1. Interior Design - Emotion-powered lights can be leveraged in interior design to provide a personalized touch and create an ambient atmosphere based on the mood of occupants.
2. Marketing - Data collected through social media platforms can help marketers design campaigns with personalized messages, target specific audiences, and predict consumer sentiment.
3. Healthcare - Emotion-powered technologies can be leveraged in healthcare to monitor and predict patient moods, detect early warning signs, and in telemedicine to provide more personalized care.