Recently, many countries like Japan, China and the USA have been the victimized by natural disasters resulting in many deaths and damages in millions of dollars. However much precautionary measures had been taken by evacuating thousands of people and preparing for the disasters, the natural disasters still proved to be too strong. However, Roger Wang, Lecturer of Fluid Mechanics in Civil Engineering, University of Dundee thinks that Aritificial Intelligence could prove to have a great potential in mitigating the consequences of natural disasters.

Over the past years, AI has developped significantly. It has also caught up to human understanding as esearchers recently demonstrated that AI could help diagnose breast tumours from the medical imaging. Roger Wang demonstrated in his research paper that AI is able to help monitor floods and could deliver more accurate early warning messages in the near future.

In his research paper, he described how he used two of the most popular AI techniques to monitor tweets and photos streamed from Twitter and a mobile app called MyCoast. These AI-based algorithms can identify the location mentioned in a tweet about flooding and describe the content of the photos to recognise flood scenes through intensive training with “worked examples”, photos manually labelled by humans using keywords. After such training, the trained AI could make a prediction about whether a new photo is a flood scene or not. However, he also mentioned that AI is better than humans in terms of speed and volume, but not in terms of quality. This is especially true of flood monitoring. His research demonstrated that AI could make mistakes in recognising flood scenes. However, this situation might change in the future. Secondly, he mentioned that AI is still weak when it comes to prediction. Although these algorithms can make acceptable forecasts within the scope of the past, predictions become wild when they go beyond the parameters of the training data. In terms of flood-monitoring, then, it is difficult to predict long-term flood trends based on the past training datasets because climate change is fundamentally changing the trend of many hydrological factors. We have no acceptable training data in this case.

Anyway, the most significant difference between AI and humans is that we generate creative solutions, and AI is not capable of providing them. It is merely a tool to facilitate humand understanding and preditcion. It has therefore a long way to go before it catches up with human thinking, creativity and motivation according to Wang (2018).

Evidently it would be a major step towards the future if AI could help us predict natural disasters sooner and help mitigate them more effectively which could save thousands of lives and millions of dollars. With the development which AI is going through nowadays, I think that within 10 years this will be possible. Only time will tell us if this prediction is accurate.

References:

Wang, R., Mao, H., Wang, Y., Rae, C., & Shaw, W. (2018). Hyper-resolution monitoring of urban flooding with social media and crowdsourcing data. Computers & Geosciences,111, 139-147. doi:10.1016/j.cageo.2017.11.008

Wang, R. (2018, September 19). AI could help us manage natural disasters – but only to an extent. Retrieved September 19, 2018, from http://theconversation.com/ai-could-help-us-manage-natural-disasters-but-only-to-an-extent-90777

The Internet of Things (IoT) has the potential to radically change the way we interact with our surroundings. The IoT digitizes the physical world by sensors which are embedded in everyday physical objects that are linked through wired and wireless networks. These sensors can send and receive data which allows us to monitor and manage objects in the physical world, electronically. The application of the IoT provides great opportunities for a wide variety of industries, from home automation to production optimization.

Throughout the years we have seen quite an interesting array of IoT applications like LG’s smart fridge and Samsungs Smart Air Dresser. However, in August 2018, IBM has filed a patent for an IoT application which might sound silly to many people, namely a ”coffee delivery drone”. According to BBC, IBM has stated that the drone can identify the “cognitive state” of office workers and lower cups of coffee on an “unspooling string”. The drone would use sensors and artificial intelligence (AI) to track things such as blood pressure, pupil dilation, and facial expressions to determine if a worker is getting tired and then hover over to provide a cup of coffee to the employee. Also, as stated in the patent, motion sensors could let thirsty workers use hand gestures to call for a pick-me-up. Additionally, the drone could pour the coffee directly into a cup on the worker’s desk, or just drop a sealed bag of hot liquid onto the desk. It could even include a heater to make sure the coffee was delivered hot. In fact, the drone system’s AI could create and store profiles of all the workers in the office, both as individuals and groups, making it easy to deliver everyone’s “regular” order without having to engage in an ongoing dialog according to Fredric Paul from Network World.

IBM has not revealed whether they would actually produce it but it requires a great amount of resources to file a 16-page patent like this. Critics like Fredric Paul have slammed this invention and questioned IBM’s focus and whether an invention like this is going to fulfill IoT’s enormous promise which the vendors and analysts all predict? My opinion on this IoT application is more nuanced, I think that silly sounding IoT innovations like this can spark more tech giants to tap into the value of IoT and come up with more valuable IoT applications. After all, many innovations sounded silly at first right?