Reduce food wastage with IoT Solution

Ethylene gas is produced by most plants, which use it as a hormone to stimulate growth & ripening. Fruits and flowers under stress can overproduce ethylene, leading them to ripen prematurely. 

Every year supermarkets lose considerable amount of their fruits and vegetables to spoilage. 

Now sensors are available that can detect ethylene gas that indicates when fruits ripen, which could be useful in preventing food spoilage. Once these sensors are integrated with IoT cloud, supermarkets will have the data on the expected impact on produce quality, as well as sensors integrated with IoT can provide alerts to ensure that products are handled & cooled correctly. Based on the data received in IoT, insights can provide dashboards/reports/alerting that enable smarter decisions to maximise shelf life of produce (longer lasting freshness for bananas) and improve the consumer experience. 

A data driven solution (ethylene sensors integrated with IoT) can expand the availability of fresh, high quality produce and minimise food wastage.

IoT and opportunities for Analytics, Artificial Intelligence & Machine Learning

IoT is not just for establishing connections between devices and systems. IoT is opening up opportunities for Analytics, AI Artificial Intelligence and Machine Learning ML. 

IoT tools can act on the numerous data sources available from various devices, sensors, and systems. Organisations can have comprehensive view of their customers’ requirements in a way that wasn’t previously possible and can then use those insights to improve the overall customer experience.

A great example would be, IoT has the potential to transform the way Healthcare is delivered. Patient’s vitals monitoring device such as Glucose Levels, Blood Pressure & Heart-Rate are being connected to the IoT which then enables the capability to share real-time patient information. Analysis of the data obtained from patient monitoring devices can be used to provide inputs to patient control devices like ventilators, defibrillators, etc.

- Use of IoT sensor enabled cameras at Airports to detect passenger queues at various check points

- Use of IoT sensors at Shopping centers to detect broken escalators, dirty washrooms

- Using IoT sensors, Supermarkets in UK can regulate the temperature of refrigerators & ovens to keep it at optimum temperatures which can reduce energy consumption & reduce food wastage by keeping food at the right temperatures. IoT can monitor the refrigerators temperature in real time & as soon as the temperature of a particular refrigerator goes above/below the optimum levels, IoT can assist in setting the temperature of refrigerator back to the optimum level. This will also help in reducing the greenhouse gas emissions from thousands of refrigerators used in Supermarkets across UK.

- IoT can play a big role in driving automation and controlling with building heating and cooling systems, which are heavy energy consumers. IoT sensors can detect how many people are there inside the store in real time, this can then be used to automatically turn off the system when customers have left, thus conserving energy. Again will help in reducing the greenhouse gas emissions

- Walmart installed IoT water monitoring systems to water the grass at 1,000 stores in 2009, and saw a 33% reduction in total water consumption over the next five years.

- A report by Ericsson states that, IoT could help reduce greenhouse gas emissions by up to 15%, across all industrial sectors by 2030

- Using the IoT and Cloud platform, fishermen with smartphones can now upload geo-located images of the sea mammals via a mobile app. This data can then be analysed to put together recommendations for future protection areas.

Edge Computing

Compared to cloud computing, where we access centralized services, edge computing refers to decentralized data processing where computing is done at or near the source of the data, instead of depending on the cloud which is diverts the traffic to one of the data centers to do all the processing. But that doesn’t mean the cloud will disappear, instead the cloud is coming closer to you.

 A simple example…for instance, if you have one Pressure sensor device which continuously sends pressure readings to the cloud. However if you have 100 x Pressure sensor devices across a factory/warehouse, you have a bandwidth problem. But if the sensor devices are “smart enough” (possibility for AI / ML) to only send the important readings and discard the rest, your internet bandwidth is saved.

One more example would be Alexa….with local speech recognition, Alexa only sends text to the cloud rather than voice recordings which results in much faster response, especially for commands that can be handled without leaving your home (e.g., turning on the light).

There is a view that there isn’t much growth left in the cloud space as nearly everything that could have been centralized has been already centralized, which then creates new opportunities for bringing the cloud closer to the edge.

The idea of edge computing is to process data on the spot if not fully at least partially at the end device to save resources (internet bandwidth, response times, etc.) while still benefiting from the advantages of the cloud.

At an enterprise level when we discuss edge to cloud, they typically are thinking about storing and processing data generated by employees or IoT devices, at the point where it is created and consumed (at the edge). Leveraging edge to cloud architectures can result in cost savings, improved productivity, without compromising on application responsiveness. This requires the use of resources that are not permanently connected to the network, such as sensors, tablets, controllers, etc.

IoT connected devices can best use the edge computing architecture. With remote sensors installed on machines or devices, they generate considerable amounts of data. If that data is sent across a long network link to be analyzed, tracked & processed, that takes much more time than if the data is processed at the edge, close to the source of the data.

With edge computing, security also improves as encrypted files are processed closer to the network core. Though edge computing supports real time requirements on the IoT, however for processing or storing large amount of data it needs the power of cloud computing.

The Amazon Web Service’s Snowball Edge device is a device with on-board storage and compute power for select AWS capabilities. Snowball Edge can carry out local processing and edge computing workloads and also transfer data between your local environment (devices, sensors, tablets, etc) and the AWS Cloud. AWS Snowball Edge brings the power of the AWS Cloud to your on premises location, which can cut down on the bandwidth because we can either do all of the processing on the device or pre-process it before sending it on to the cloud.

Edge to cloud file services enable companies to manage their data centrally in the cloud, while at the same time making that data instantly available to users at the edge. By having edge to cloud file services, enterprises can improve application responsiveness and availability. This enables agile collaboration, while also providing data security, governance and compliance. Edge to cloud file services will be a key enabler for business success by offering low latency, reliable access to data & power of cloud-scale economics.

Low Code Application Platforms - LCAP

The pandemic has forced businesses to rapidly transform their operating models. Businesses are adopting several Digital Transformation initiatives to address the challenges of the new normal. There is demand for businesses to be more flexible & agile and as a result businesses are looking to adopt Low Code Application Platforms LCAP. There is increasing demand for low-code platforms that fast-track app development and this demand is driven by the need for close collaboration between IT and business teams.

What is LCAP?

Low-Code application platform offers rapid application development and deployment using low or no techniques. Low-Code makes exploring & integrating latest emerging technologies like AI, ML and IoT accessible for business users and developers with drag & drop ease, enabling them to create functional prototypes. Low-Code platforms also enables business users to build Apps with little to no coding experience. With Low-code platforms, developers can work using existing templates and drag prebuilt elements, forms, and objects together to get a simple working app.

The components of Low-Code platform include: access to AI, ML, IoT without having the need for domain expertise, automated testing, fast integration, reusability, DevOps, one click deployment to the Cloud that automatically manages application reliability & scalability. For example, Low-code application platforms provide flexible integration options through which organisations can connect their disparate systems which may include legacy, on-premise systems or cloud based systems and have a unified view of their data.

Fintechs and Conventional Bankers

Fintechs companies have brought a wave of insecurity among conventional bankers. Fintech companies introduced dynamic payment systems that empowered their users to complete their financial transactions without the involvement of a middleman and limiting transaction charges applied on them by traditional banks. Fintechs have increased the speed of transactions. Technology has helped fintech organizations in improving transparency of transactions in their payment systems which led to improved user interaction and experience.

Conventional Banks have set financial services such as ATMs and online banking, their innovation skills are reliable. Building their services like the fintech companies can significantly help traditional banks in avoiding risks posed by fintechs. Developing & implementing similar services could be challenging but could yield ample benefits in the long run for traditional banks. 

Threat of Fintech to banks is real and banks have to start searching for viable options for working in the market alongside fintechs. Banks can think of partnering with fintech companies, acquire or develop a fintech portal that can create a digital value of banks.

Dark Data and ML

Data can be categorised into 3 categories:

• Critical Business Data: this is the data that is required for the day to day operations of the business, it allows the business to grow
• Trivial Data: this data is never used and has no importance to the business
• Dark Data: this is the data that is hiding within your internal systems, folders, sources and networks and can hold a large amount of information that can be useful for business and can be moved to Critical Data Set category.

According to a recent IBM study, over 80% of all data is dark and unstructured. IBM estimates that this will rise to 93% by 2020. Dark Data examples:

• Spreadsheets • Analytics Reports and Survey Data • Multiple old versions of documents • Email attachments that are downloaded and then ignored • Inactive databases with unused customer • Inactive databases with unused customer information • Project notes and learning's

Basically Dark Data is the data that is left behind from various processes, scattered across every level of business. Some people may consider it as unnecessary and ignore it, whereas it can be highly valuable for making business decisions.

To handle Dark Data spread across different types of spreadsheets, emails, zip files, documents and images stored on various servers, the power of Machine Learning algorithms can be used. AI, Machine Learning and Analytics can systematically identify the rarely used data and indicates that data is obsolete.

Aggregation of data may be required for queries which then would need integration to access the data from different sources. Machine Learning can make the process efficient by automatic mapping between the sources and data repository.

 

Post Corona - Path back to Growth

There is no single number or data that could tell what would be the impact of Covid-19 could be on the world economy. Reaction of firms, company's, and businesses are unknown.

 

We are seeing melt down in the global financial market and may indicate that the world economy is on the path of recession. Though the recession risk is there, but let us not take it as a forgone conclusion.

 

Path back to growth will depend on many factors:

 

World economy will be different after the pandemic like Covid-19 in a number of ways - crisis can spur the adoption of New Technologies and Business models.

• As Schools have closed in many parts of the world could e-learning mode of delivery of education see a smart break through. While online education is helping to cope with the current emergency, it is also preparing the world for the next future. It is a great idea to build your trusted platform for learning.
• Digital efforts to track coronavirus spread via smartphone trackers demonstrates a powerful new public health tool.
• There is need for a robust delivery management solution - finding ways to reach customers doorstep.
• Take grocery store online to ensure timely delivery of grocery orders at customers’ doorstep
• App based payments to avoid handling cash and reduce their potential exposure to COVID-19
• At this moment, pharmaceutical company's have an essential role to play. People quarantining themselves find it difficult to reach medical stores. Not only those affected by the virus, but others who are dealing with minor or major health issues, are failing to get medicines on time.  With right technology, online medicine ensure timely delivery of medicine's at peoples doorstep
• On-Demand Doctors , Nurses , Caretakers - build apps which simplifies the process of booking for medical professionals visiting home
• Fitness & Wellness App - people are increasingly turning to digital workout programs to maintain their exercise routines from home. From online training apps to yoga and meditation apps, the sector promises tremendous growth

Keep calm retain your confidence, communicate with people and teams, make them comfortable, actively collaborate with your partners, reach out to the community.

 

Work from home is the new normal -  worldwide there are millions of remote workers. As we settle down to new routines it is also making us question a constant need to travel during normal times, it is also making us understand new ways of keeping virtual teams engaged.

 

The transformation of work in organisations is being shaped by technology and talent. Faster computing power, connected devices, Cloud, Blockchain, RPAs are redefining the man machine interface.

 

Routine and mono skilled roles will be replaced with specialists. Skills like creativity, empathy, collaboration will gain more prominence, as will be there requirement for data scientists, design and systems thinking.

 

Post Covid-19 world would be led by key enablers like Technology, high level of social skills to connect virtual teams, it will require flexible work policies that allows for people to choose work times that work for them and their role, and leadership that solicits participation and not hierarchy and its purpose led and not power driven.

 

Acquiring New Skills, Continuous Learning, Expertise, Domain Skills, Leadership Skills - never ever lose sight of them.