MYERS AN APARTHEID BENEFICIARY
SPARE US EXCUSES AND FIX SANRAL
IT WAS WITH some disbelief and shock that I waded through the article where the chief executive of Sanral appeared to blame everyone other than himself for the current woes in the South African road building industry.
I have, as an investment analyst, covered the South African construction sector for more than 20 years. Throughout the majority of this period Sanral has stood out as a beacon of efficient, consistent and effective government spending.
Mr Skhumbuzo Macozoma inherited a national road network that was the envy of many countries worldwide.
I was the analyst that, at the recent Raubex investor presentation, asked the management team specifically what was happening at Sanral.
After reading his article I still lack any understanding of the current impasse. Macozoma has failed to explain exactly what the issues are between Sanral and the Treasury and how this organisation functioned for 18 years before his arrival. What has changed? I really cannot accept that he is working “tirelessly” on these issues 18 months later.
While I fully accept that the construction industry woes should not be fully dumped on Sanral’s shoulders, there clearly have been a myriad “own goals” scored by the vast majority of the players. That said, the lack of work coming out of Sanral has directly resulted in a significant number of job losses at all levels, for which he must stand up and assume full responsibility for.
Let’s just hope that once Sanral finally gets its act together we’ll still have a construction industry with the requisite skills, equipment and resources to perform the work to the high standards and cost efficiency that we as South Africans have become accustomed to.
The time for excuses are over, let’s sort this debacle out before our national road network becomes the next state-owned enterprise that is admitted into intensive care!
Written in my personal capacity IN HIS LETTER Mr Myers (Business Report), November 22) says Discovery will be giving away 10 percent of the equity (in the new bank) “on a purely racist basis”.
Will Myers concede that he and his ancestors were beneficiaries of an economic and political system that entrenched whites-only property ownership (of the most valuable land), whites-only ownership of mineral rights, whites-only job reservation, and so on and so on?
Does Myers think that in the 1960s a black person could walk into the stock exchange and have a discussion about a stock exchange listing and capital raising?
A black person wouldn’t be able to go into the restroom or eat in the canteen, besides needing a “dompass” to be in a place reserved for whites – has Myers forgotten this?
In 1994, no whites were made to pay (financially) for the havoc apartheid had wreaked on black people. No white people’s assets were seized.
So Mr Myers, if you will concede that you, and other white people like you will pay and make financial reparations for apartheid, I will stand up and speak out for black economic empowerment shares to be issued to you.
Via e-mail THE INTERNET of Things (IoT) plays a major role in the realisation of the Fourth Industrial Revolution. But what is this IoT that everybody talks about?
The IoT is an interconnection of computing devices and sensors embedded in everyday objects. These objects – devices, vehicles, machines, smart home appliances, and other items – constantly collect and exchange data via the internet. Currently, about 17 billion smart devices and sensors are connected to the internet and can be remotely monitored and controlled.
As a result of cheap processors and wireless networks, it is possible to turn anything, from a pill to an aeroplane engine, into part of the IoT. This enables devices that would normally be dumb to collect and transmit data without human involvement.
The IoT is built on many innovative technologies, such as application programming interfaces (APIs), which connect devices to the internet and makes the creation of applications and extraction of data possible.
Smart devices and commodity sensors generate an immense amount of data that are analysed in real time and used to make improvements. This is where predictive analytics and Big Data management tools become useful. Artificial intelligence (AI) and machine learning are also used to add context to data and activate actions without any human intervention.
Other keys IoT technologies are the cloud and radio frequency identification (RFID) chips. Cloud-based IoT platforms gather device data, link devices to back-end systems, ensure IoT interoperability, and run IoT applications, while RFID tags – lowpower chips that communicate wirelessly – are used to capture digital data encoded in badges, cards, or smart labels to help track the location of people or equipment.
The first ”smart device“was linked to the internet already in 1982, when a modified Coke machine at Carnegie Mellon University became the first internet-connected appliance, able to report its inventory and the temperature of replenished drinks.
Since the first connected machine, IoT technologies disrupted many traditional business models and established huge opportunities for companies to create new services based on real-time sensor data. It is often used to automate business and manufacturing processes, remotely monitor and control operations, optimise supply chains, and conserve resources. One of the biggest benefits of the IoT is that it allows people and companies access to more data about products and internal systems, and thus a greater ability to make changes as a result.
We are currently in the first generation of IoT, mostly collecting data from dumb devices and sensors, whereafter it is aggregated in centralised cloud solutions. In the coming generations, we will see much more of edge analytics, intelligent networks and IoT devices as actuators.
The IoT is indeed getting smarter. Companies are incorporating artificial intelligence – in particular, machine learning – into their IoT applications to automatically identify patterns and detect anomalies in smart sensor and device data such as temperature, pressure, air quality, humidity, vibration, and sound. It has been proven that machine learning can make operational predictions up to 20 times earlier and with greater accuracy.
AI applications for IoT further enabled companies to avoid costly unplanned downtime of equipment. Predictive maintenance – using machine learning and analytics to identify patterns in the constant streams of machine data – can predict equipment failure ahead of time with a reduction in planning time of 20 to 50 percent, an increased uptime of 10 to 20 percent and a cost-saving of 5 to 10 percent.
Just as machine learning can predict equipment failure, AI-powered IoT can also predict operational efficiency by processing constant streams of data and finding patterns invisible to the human eye. The IoT sensors and machine learning tools of a shipping fleet operator established that cleaning the hulls more often – an expensive, downtime-causing exercise – actually increased the fleet’s overall profitability since smooth hulls enhance fuel efficiency enough to outweigh the increased cleaning costs.
Similarly, predictive IoT are used to discover fraudulent behaviour at bank ATMs, predicting car driver insurance premiums based on driving patterns of the driver, identifying potentially dangerous stress conditions for factory workers, and monitoring law enforcement surveillance data to determine likely crime scenes ahead of time.
The IoT also combines with the power of artificial intelligence, blockchain, and other emerging technologies to create “smart hospitals” of the future. Medical devices, patient monitoring tools, wearables, and other sensors send data to the cloud via the internet.
The data is then analysed and actionable insights for chronic disease management are created. Predictive analytics becomes very important to predict the deterioration of patients with implanted cardiac devices, internet-connected ventilators, imaging systems, vital signs monitors, and anaesthesia machines.
Strangely enough, AI and the IoT are even changing the way we watch golf. The PGA Tour collects 32 000 data points at every event, and they have about 174 million shot attributes in their database. Using advanced analytic tools and machine learning to review all the data, they provide broadcasters with compelling ideas and concepts that they can use to create personalised stories.
Professor Louis Fourie is the deputy vicechancellor: knowledge & information technology at Cape Peninsula University of Technology.